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Image analysis and computer vision: 1989
COMPUTER VISION, GRAPHICS, AND IMAGE PROCESSING 50,
188-240 (1990)
SURVEY Image Analysis and Computer Vision: 1989” AZRIEL
ROSENFELD
Center for Automation Research, University of Maryland, College Park, Maryland 20742-3411
Received January lo,1990 This paper presents a bibliography of nearly 1200 references related to computer vision and image analysis, arranged by subject matter. The topics covered include architectures; computational techniques; feature detection, segmentation, and image analysis; matching, stereo, and time-varying imagery; shape and pattern; color and texture; and three-dimensional scene analysis. A few references are also given on related topics, such as computational geometry, computer graphics, image input/output and coding, image processing, optical processing, visual perception, neural nets, pattern recognition, and artificial intelligence. 0 1990 Academic Press, Inc.
1. INTRODUCTION
This is the twentieth in a series of bibliographies on computer processing of pictorial information, covering primarily items published during 1989. The coverage is restricted, for the most part, to a selected set of U.S. or international journals and proceedings of specialized meetings. No attempt is made to summarize or evaluate the items cited; the purpose is simply to provide a convenient compendium of references, grouped by subject. The references are arranged under the following headings: (A) (B) (0 (D) (E) (F) (G) (H) (I) (J)
General references Related topics Applications Architectures Computational techniques Feature detection, segmentation, image analysis Matching, stereo, time-varying imagery Shape and pattern Color and texture Three-dimensional scene analysis.
Letter/number codes in the text (A.l, etc.) correspond to sections of the bibliography. *The support of the Air Force Office of Scientific Research under Grant AFOSR-860092 is gratefully acknowledged, as is the help of Sandy German in preparing the bibliography. 188 0734-189X/90 $3.00 Copyright 0 1990 by Academic Press, Inc. All rights of reproduction in any form reserved.
IMAGE
ANALYSIS
AND
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Papers, books, etc. relating primarily to specific topics will be cited in later sections. In this section we cite references that relate to more than one topic: (A.0 Meetings and meeting proceedings [l-23] (A.2) Textbooks [24-261, a journal [27], some general papers 128-301,descriptions of research at various institutions [31-441, and the previous bibliography in this series [45]. 2. RELATED
TOPICS
The following related areas are not covered systematically, but we give a few references on them: (B.l) Computational geometry: Meetings, special issues, etc. [46-511. (B.2) Computer graphics: Meetings, etc. [52-631. (B.3) Image input/output [64-671, digitization [68-721, and coding [73-741. (B.4) Image processing (multidimensional signal processing, enhancement, restoration, reconstruction&general references [75-781, as well as papers on image smoothing [79-971 (see also [98]) and contrast enhancement [99-1011. (B.5) Optical processing [102-l 111. (B.6) Visual perception: meetings [112-1141, as well as a few books [115-1221 and papers [123-1261. (A few other papers on specific aspects of perception are cited in later sections.) (B.7) Neural networks, connectionism 2127-1531(see also [154-1561 on learning). (B.8) Pattern recognition and artificial intelligence: some general references [157-1691, as well as some papers on constraint satisfaction and relaxation methods [170-1761. 3. APPLICATIONS*
(C.l) Character recognition, document processing [ 177- 1781. (C.2) Biomedical applications [179-1831. CC.31Industrial applications [184-1961, including some general references on robotics applications [197-2001. (C.4) Autonomous systems [201-2061 (robot navigation, etc.), including some individual papers [207-2191. (C.5) Remote sensing, reconnaissance [220-2271, including some individual papers [228-2411. (C.6) Other applications [242-2431. 4. ARCHITECTURES
CD.11 General references [244-2571. (D.2) Meshes, hypercubes, etc. [258-2751. *Individual
papers on most of these topics are no longer cited in this bibliography.
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(D.3) Other systems [276-3011. (D.4) Related topics [301-3091. 5. COMPUTATIONAL
TECHNIQUES
(E.l) Image operations (convolutions, morphological operations, etc.) [310-3281. (E.2) Multiresolution and scale space methods [329-3421. (E.3) Geometric transformations, calibration [343-3621. (E.4) Interpolation, function fitting, etc. [363-3991 (see also [400-4021). 6. FEATURE
DETECTION,
SEGMENTATION,
AND
IMAGE
ANALYSIS
(F.l) Feature detection [403-4381. (F.2) Segmentation [439-4741. (F.3) Image analysis [475-4931. See also [494-5051 on geometry theorem proving and [506-5101 on grammars and automata, as well as [511-5121. 7. MATCHING,
STEREO,
AND
MOTION
(G.l) Image, template, and shape matching [513-5371; see also [538-5511 on Hough transforms, and [552-5661 on string, array, tree, graph, and point pattern matching. (G.2) Stereo 1567-5951. (G.3) Motion [596-7171 (see also [718-7261 on motion perception). 8. SHAPE
(H.l) Representations [727-7371; topology [738-7511. See also [752-7571 on geometric precision. (H.2) Lines and curves [758-7771 (see also [778-7801). (H.3) Distance and skeletons 1781-8061. (H.4) Properties and recognition [807-8321 (see also [833-8351X (H.5) Motion and path planning [836-8681; see also [869] on labyrinth searching, and [870-8771 on map building and learning. 9. COLOR
(1.1) (1.2) (1.3) (1.4)
AND
TEXTURE
Illumination and color [878-8881. Texture: models, synthesis [889-9101. Texture: description [911-9181. Texture: segmentation [919-9291. 10. THREE-DIMENSIONAL
SCENE ANALYSIS
(J.l) 3D data acquisition [930-9481 and analysis (feature detection, segmentation, property measurement) [949-9571; see also [958-9591 on 3D images and [960-9651 on grasping and machining. (5.2) Inference of 3D data from images (“recovery”) [966-10151.
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(5.3) 3D shape and models (surfaces and solids) [1016-10771; physically-based models [1078-10871 (see also [1088]>. (5.4) Image synthesis [1089-11271 (see also 111281). (J.5) 3D object recognition [1129-11661. (5.6) M iscellaneous topics (multisensor systems, sensor control, etc.) [1167-11871. REFERENCES
For brevity, the following frequently cited sources are cited in abbreviated forms: A. Conference Proceedings Abbreviation
Conference
AAAI CG CVPR IJCAI IUW SIGGRAPH WI3DS WVM
National Conference on Artificial Intelligence Symposium on Computational Geometry Conference on Computer Vision and Pattern Recognition International Joint Conference on Artificial Intelligence Image Understanding Workshop SIGGRAPH’89 Conference Workshop on Interpretation of Three-Dimensional Scenes Workshop on Visual Motion
Abbreviation
Journal
AI BC C&G CGA CVGIP DCG IJCV IJPRAI
Artificial Intelligence Biological Cybernetics Computers and Graphics IEEE Computer Graphics and Applications Computer Vision, Graphics, and Image Processing Discrete and Computational Geometry International Journal of Computer Vision International Journal of Pattern Recognition and Artificial Intelligence International Journal of Robotics Research Information Processing Letters Image and Vision Computing Journal of Computer and System Sciences Journal of the Optical Society of America Journal of Parallel and Distributed Computing Machine Vision and Applications Parallel Computing Proceedings of the IEEE Pattern Recognition Pattern Recognition Letters SIAM Journal on Computing Signal Processing IEEE Transactions on Acoustics, Speech, and Signal Processing IEEE Transactions on Computers
B. Journals
IJRR IPL IVC JCSS JOSA JPDC MVA PC P-IEEE PR PRL SIAM JC SP T-ASSP T-COMP
192
AZRIEL T-PAM1 T-RA T-SMC TCS TOG VC
ROSENFELD
IEEE Transactions on Intelligence IEEE Transactions on IEEE Transactions on Theoretical Computer ACM Transactions on The Visual Computer
Pattern Analysis and Machine Robotics and Automation Systems, Man, and Cybernetics Science Graphics
A. General References A. 1. Meetings 1. A. Krzyzak, T. Kasvand, and C. Y. Suen, eds., Computer vision and Shape Recognition (Vision Interface 88, Edmonton, Alberta, June 6-10, 1988), World Scientific, Singapore, 1989. 2. J. C. Simon, ed., From Pixels to Features (Proceedings of a workshop held in Bonas, France, August 22-27, 19881, North-Holland, Amsterdam, 1989. 3. Special Issue: 4th Alvey Vision Conference (Manchester, UK, August 31-September 2, 19881, NC 7 cl), February 1989,3-78. 4. Multi-site Seminar in Vision, Tel Aviv, Israel, March 17, 1989. 5. Proceedings, Image Understanding Workshop (Palo Alto, CA, May 23-26, 1989), Morgan Kaufmann, San Mateo, CA. 6. Proceedings, CVPR’89 (IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Diego, CA, June 4-8, 19891, Computer Society Press, Washington, DC. 7. Image Understanding and Machine Vision (Optical Society of America Topical Meeting, North Falmouth, MA, June 12-14, 1989), Optical Society of America, Washington, DC. 8. M. Pietiklinen and J. Rohning, eds., Proceedings of the 6th Scandinavian Conference on Image Analysis (Oulu, Finland, June 19-22, 19891, Pattern Recognition Society of Finland, 1989. 9. IBM Europe Institute on Common Topics in Image Analysis and Synthesis, Garmisch-Partenkirchen, FRG, July 10-14, 1989. 10. Third International Conference on Image Processing and its Applications (Warwick, UK, July 18-20, 1989), Institution of Electrical Engineers, London, UK, 1989. 11. Active Perception and Robot Vision (NATO Advanced Study Institute), Maratea, Italy, July 17-28, 1989. 12. A. G. Tescher, ed., Applications of Digital Image Processing XII (San Diego, CA, August 8-11, 1989), l+oc. SPIE 1153. 13. CAIP’89, Third International Conference on Computer Analysis of Images and Patterns, Leipzig, DDR, August 31-September 2, 1989. 14. From Pixels to Features (COST 13 Summer School), Bonas, France, September 4-9, 1989. 15. ICIP’89, IEEE International Conference on Image Processing, Singapore, September 5-8, 1989. 16. SICIAP, 5th International Conference on Image Analysis and Processing, Positano, Italy, September 20-22, 1989. 17. ASOIZ’89, Third Conference on Automated Systems of Image Processing, Leningrad, USSR, September 24-27, 1989. 18. AIPR, 18th Workshop on Applied Imagery Pattern Recognition, Washington, DC, October 11-13, 1989. 19. D. Casasent, ed., Intelligent Robots and Computer Vision VIII: Algorithms and Techniques (Philadelphia, PA, November 6-10, 19891, Proc. SPIE 1192. 20. B. G. Batchelor, ed., Intelligent Robots and Computer Vision VIII: Systems and Applications (Philadelphia, PA, November 9-10, 19891, Proc. SPZE 1193. 21. P. S. Schenker, ed, Sensor Fusion II: Human and Machine Strategies (Philadelphia, PA, November 6-9, 1989), Proc. SPZE 1198. 22. W. A. Pearlman, ed., Visual Communications and Image Processing IV (Philadelphia, PA, November S-10, 19891, Proc. SPZE 1199. 23. Proceedings, Workshop on Interpretation of 3D Scenes (Austin, TX, November 27-29, 1989), Computer Society Press, Washington, DC.
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A.2. Books, etc. 24. M. C. Fairhurst, Computer Vision for Robotic Systems-An Introduction, Prentice Hall, New York, 1988. 25. A. K. Jain, Fundamentals of Digital Image Processing, Prentice Hall, Englewood Cliffs, NJ, 1989. 26. R. J. Schalkoff, Digital Image Processing and Computer Vkion, Wiley, New York, 1989. 27. G. Wade, E. A. Robinson, and H. Lee, eds., International Journal of Imaging Systems and Technology, Wiley, New York, 1989ff. 28. J. R. Kender, Some issues for the panel on methodology and standards in CVPR research. CVPR, 436. 29. R. M. Haralick, Methodology for experimental computer vision, CVPR, 437-438. 30. D. Petkovic, The need for accuracy verification of machine vision algorithms and systems, CVPR. 439-440.
31. R. L. Simpson, An update on strategic computing computer vision, IUW, l-11. 32. M. A. Fischler and R. C. Belles, Image understanding research at SRI International, IUW, 21-31. 33. T. Kanade and S. Shafer, Image understanding research at Carnegie Mellon, IUW, 32-47. 34. A.R. Hanson and E. M. Riseman, Progress in computer vision at the University of Massachusetts, IUW, 49-55. 35. T. Poggio and the staff, MIT progress in understanding images, IUW, 56-74. 36. R. Nevatia, K. Price, and G. Medioni, USC image understanding research: 1988-89, IUW. 75-93. 37. A. Rosenfeld, L. S. Davis, and J. (Y.) Aloimonos, Image understanding research at the University
of Maryland (January 1988-February 19891,IUW, 94-109. 38. J. R. Kender, P. K. Allen, and T. E. Boult, Image understanding and robotics research at Columbia University, IUW, 110-121. 39. C. M. Brown and R. C. Nelson, Image understanding at the University of Rochester, IUW. 122-127. 40. N. R. Corby, Image understanding research at GE, IUW, 144-146. 41. C. Bjorklund, M. Noga, E. Barrett, and D. Kuan, Lockheed imaging technology research for missiles and space, IUW, 332-352. 42. R. M. Bolle, A. Califano, R. Kjeldsen, and R. W. Taylor, Computer vision research at the IBM T. J. Watson Research Center, IUW, 471-478. 43. E. M. Riseman and A. R. Hanson, Computer vision research at the University of Massachusetts -themes and progress, IJCV 2, 1989, 199-207. 44. M. A. Fischler, An overview of computer vision research at SRI International-themes and progress, IJCV 3, 1989, 7-15. 45. A. Rosenfeld, Image analysis and computer vision: 1988, CVGIP 46, 1989, 196-264.
B. Related Topics B.l. Computation Geometry 46. H. Noltemeier, ed., Computational Geometry and its Applications, Springer, Berlin, 1988. 47. Proceedings of the Fifth Annual Symposium on Computational Geometry (Saarbriicken, FRG. June 5-7, 19891,ACM Press, New York. 48. First Canadian Conference on Computational Geometry, Montreal, Quebec, August 21-25, 1989. 49. J. O’Rourke, The computational geometry column #3, Computer Graphics 23, 1989, 212-213. 50. C. K. Yap, guest ed., Special Issue on Computational Geometry, Algorithmica 4 (11, 1989, 1-155.
51. C. Yap, guest ed., Special Issues on Computational Geometry. JCSS 39 (2), October 1989, 125-241.
B.2. Computer Graphics 52. D. F. Rogers and R. A. Earnshaw, eds., Computer Graphic Techniques, Springer, Berlin, 1989. 53. NCGA’89 (Tenth Annual Conference and Exposition, National Computer Graphics Association). Philadelphia, PA, April 16-20, 1989. 54. Proceedings, Graphics Interface ‘89 (London, Ontario, June 19-23, 1989), Morgan Kaufmann, San Mateo, CA, 1989.
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55. N. Magnenat-Thalmann and D. Thalmann, eds., New Trends in Computer Graphics (Proceedings, Computer Graphics International ‘88, Geneva, Switzerland, May 24-27, 19881, Springer, Berlin, 1988. 56. N. Magnenat-Thalmann and D. Thalmann, eds., Special Issue on Computer Graphics International ‘88 (CGI ‘88), VC 5 (l-21, 1989, 1-119. 57. R. A. Eamshaw and B. Wyvill, eds., New Advances in Computer Graphics (Proceedings, Computer Graphics International ‘89, 7th Conference of the Computer Graphics Society, Leeds, UK, June 27-30, 1989), Springer, Berlin, 1989. 58. SIGGRAPH’89 Conference Proceedings (Boston, MA, July 31-August 4, 1989), Compufer
B.3. Image I/O,
Digitization,
and Coding
64. R. R. Morton and R. C. Hsieh, eds., Imaging Workstations and Document Input Systems (Los Angeles, CA, January 17-20, 19891, Proc. SPIE 1074. 65. G. M. Nelson, guest ed., Visualization in Scientific Computing, Computer 22 (8), August 1989, 10-101. 66. Imaging ‘89 (Sixth Annual International Electronic Imaging ‘89 East Exposition and Conference), Boston, MA, October 2-5, 1989. 67. Imagexpo (International Imaging Industry Conference and Exposition), Vienna, Austria, October 18-20, 1989. 68. S. B. M. Bell, F. C. Holroyd, and D. C. Mason, A digital geometry for hexagonal pixels, NC 7, 1989, 194-204. 69. J. D. Hobby, Rasterizing curves of constant width, J. ACM 36, 1989, 209-229. 70. B. Kamgar-Parsi and B. Kamgar-Parsi, Evaluation of quantization error in computer vision, T-PAMI
11, 1989,929-940.
71. B. Kamgar-Parsi, B. Kamgar-Parsi, and W. A. Sander III, Quantization error in spatial sampling: comparison between square and hexagonal pixels, CVPR, 604-611. 72. N. Gharachorloo, S. Gupta, R. F. Sproull, and I. E. Sutherland, A characterization of ten rasterization techniques, SIGGRAPH, 355-368. 73. L. Chariglione, ed., Signal Processing: Image Communication-Theory, Techniques, and Applications, Elsevier, 1989ff. 74. H. G. Musmann, guest ed., Special Issue on 64kbit/s coding of moving video, Image Communication 1 (21, October 1989, 83-243.
B .4. Image Processing 75. J. Biemond, guest ed., Special Issue on Multidimensional Signal Processing (Part II), SP 16 (0, January 1989, l-82. 76. J. Duvemoy, ed., Image Processing III (Paris, France, April 24-28, 19891, Proc. SPIE 1135. 77. N. K. Bose, M. Simaan, and J. Biemond, eds., Multidimensional Systems and Signal Processing, Kluwer, 1990ff. 78. Sixth Workshop on Multidimensional Signal Processing, Monterey, CA, September 6-8, 1989. 79. S. J. Willson, Convergence of iterated median rules, CVGIP 47, 1989, 105-110. 80. P. W. Verbeek and B. J. H. VeMrer, 2-D adaptive smoothing by 3-D distance transformation, PRL 9, 1989, 53-65. 81. E. R. Davies, Edge location shifts produced by median filters: theoretical bounds and experimental results, SP 16, 1989, 83-96.
IMAGE ANALYSIS AND COMPUTER
VISION:
1989
19.5
82. F. Safa and G. Flouzat, Speckle removal on radar imagery based on arithmetical morphology, SP 16, 1989, 319-333. 83. J. Astola and Y. Neuvo, Optimal median type filters for exponential noise distributions, .SP 17. 1989, 9.5-104. 84. L. Naaman and A. C. Bovik, Least-squares order statistic filters with coefficient censoring, S P 18, 1989, 139-152. 85. R. Kutka, A variable median filter for image restoration adaptable to different types of spike noise, S P 18, 1989, 217-224. 86. H. U. Diihler, Generation of root signals of two dimensional median filters. S P 18, 1989. 269-276. 87. H. G. Longbotham and A. C. Bovik, Theory of order statistic filters and their relationship to linear FIR filters, T-ASSP 37, 1989, 275-287. 88. Y. H. Lee, S. J. Ko, and A. T. Fam, Efficient impulsive noise suppression via nonlinear recursive filtering, T-ASSP 37, 1989, 303-306. 89. J. T. Astola and T. G. Campbell, On computation of the running median, T-ASSP 37. 1989. 572-574. 90. F. Palmieri and C. G. Boncelet, Jr., Ll filters-a new class of order statistic filters, T-ASSP 37. 1989, 691-701. 91. S. Y. Park and Y. H. Lee, Double smoothing of images using median and Wiener filters, T-ASSP 37, 1989, 943-946. 92. A. Kundu and W. R. Wu, Double-window Hodges-Lehman (D) filter and hybrid D-median filter for robust image smoothing, T-ASSP 37, 1989, 1291-1298. 93. P. P. Gandhi, I. Song, and S. A. Kassam, Nonlinear smoothing filters based on rank estimates of location, T-ASSP 37, 1989, 1359-1379. 94. 0. Vainio, Y. Neuvo, and S. E. Butner, A signal processor for median-based algorithms, T-ASSP 37, 1989, 1406-1414. 95. C. Ray and R. K. Ward. A parametrized family of nonlinear image smoothing filters, T-ASSP 37, 1989, 1458-1462. 96. P. Saint-Marc, J. S. Chen, and G. Medioni, Adaptive smoothing: a general tool for early vision. CVPR, 618-624. 97. L. D. Cai, A “small leakage” model for diffusion smoothing of image data, IJCAI, 1585-1590. 98. J. M. Steele, Certifying smoothness of discrete functions and measuring legitimacy of images. J. Complexity 5, 1989, 261-270. 99. A. Beghdadi and A. Le Negrate, Contrast enhancement technique based on local detection of edges, CVGIP 46, 1989, 162-174. 100. K. W. Leszczynski and S. Shalev, A robust algorithm for contrast enhancement by local histogram modification. NC 7, 1989, 205-209. 101. H. Li and H. S. Yang, Fast and reliable image enhancement using fuzzy relaxation technique, T-SMC 19, 1989, 127661281.
B.5. Optical Processing 102. R. Arrathoon, Optical Computing-Digital and Symbolic, Dekker, New York, 1989. 103. H. K. Liu, ed.. Optical Pattern Recognition (Los Angeles, CA, January 17-18, 19891,Proc. SPIE 1053. 104. H. J. Caulfield, ed., Optical Pattern Recognition II (Paris, France, April 24-28, 1989), Proc. SPIE 1134. 105. B. Javidi, ed., Optical Information Processing Systems and Architectures (San Diego, CA, August 8-11, 19891,hoc. SPIE 1151. 106. J. L. Horner, guest ed., Special Section on Optical Devices and Computing, P-IEEE 77 (lo), October 1989, 1511-1583. 107. C. K. Campbell, Application of surface acoustic and shallow bulk acoustic wave devices, P-IEEE 77, 1989, 1453-1484. 108. D. L. Flannery and J. L. Horner, Fourier optical signal processors, P-IEEE 77, 1989, 1511-1527. 109. J. N. Lee and A. VanderLugt, Acoustooptic signal processing and computing, P-IEEE 77. 1989. 1.528-1557. 110. W. T. Cathey. K. Wagner, and W. J. Miceli, Digital computing with oplics, P-IEEE 77, 1989. 155881572.
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111. M. M. Eshaghian and V. K. Prasanna-Kumar, Fine grain image computations on electro-optical arrays, CVPR, 666-761.
8.6. Visual Perception 112. B. E. Rogowitz, ed., Human Vision, Visual Processing, and Digital Display (Los Angeles, CA, January 18-20, 1989), Proc. SPZE 1077. 113. Vision and Three-Dimensional Representation, Minneapolis, MN, May 24-26, 1989. 114. Workshop on Human and Machine Vision, North Falmouth, MA, June 15, 1989. 11.5. W. A. Richards, ed., Natural Computation, MIT Press, Cambridge, MA, 1988. 116. R. L. De Valois and K. K. De Valois, Spatiul I&ion, Oxford University Press, Oxford, UK 1988. 117. B. M. Bennett, D. D. Hoffman, and C. Prakash, Observer Mechanics-A Formul Theory of Perception, Academic Press, Orlando, FL, 1989. 118. M. L. Commons, R. J. Herrnstein, S. M. Kosslyn, and D. B. Mumford, eds., Behavioral Approaches to Pattern Recognition and Concept Formation, Erlbaum, Hillsdale, NJ, 1989. 119. M. Hershenson, The Moon Illusion-An Anomaly of Visaal Space Perception?, Erlbaum, Hillsdale, NJ, 1989. 120. G. Humphreys and V. Bruce, Visual Cognition: Computational, Experimentul, and Neuropsychologicul Perspectives, Erlbaum, Hillsdale, NJ, 1989. 121. B. E. Shepp and S. Ballesteros, Object Perception-Structure and Process, Erlbaum, Hillsdale, NJ, 1989. 122. R. A. Finke, Principles of Mental Imagery, MIT Press, Cambridge, MA, 1989. 123. J. B. Deregowski, Real space and represented space: cross-cultural perspectives, Behavioral Bruin Sciences 12, 1989, 51-119. 124. D. H. Ballard, Behavioural constraints on animate vision, ZVC 7, 1989, 3-9. 125. R. J. Watt, Scanning from coarse to fine spatial scales in the human visual system after the onset of a stimulus, JOSA A4, 1987, 2006-2021. 126. Z. Xie and T. G. Stockham, Jr., Toward the unification of three visual laws and two visual models in brightness perception, T-SMC 19, 1989, 379-387.
B.7. Neural Networks 127. E. R. Caianiello, ed., Parallel Architectares and Neural Networks (First Italian Workshop, Salerno, Italy, April 27-29, 1988), World Scientific, Singapore, 1989. 128. IJCNN’89, International Joint Conference on Neural Networks, Washington, DC, June 18-22, 1989. 129. Neuro-Nimes ‘89, Second International Workshop on Neural Networks and their Applications, Nimes, France, November 13-16, 1989. 130. V. Vemuri, ed., Arttjkiul Neural Networks: Theoretical Concepts, Computer Science Press, Rockville, MD, 1988. Synapses to Networks, MIT 131. C. Koch and I. Segev, eds., Methods in Neuronal Modeling-From Press, Cambridge, MA, 1988. 132. S. Pinker and J. Mehler, eds., Connections and Symbols, MIT Press, Cambridge, MA, 1988. 133. C. C. Klimasauskas, A Bibliography of Neurocomputing, MIT Press, Cambridge, MA, 1988. 134. R. E&miller and C. v. d. Malsburg, eds., Neural Computers, Springer, Berlin, 1988. 135. Y. H. Pao, Adaptive Pattern Recognition and Neural Networks, Addison-Wesley, Reading, MA, 1989. 136. M. A. Gluck and D. E. Rumelhart, eds., Neuroscience and Connectionist Theory, Erlbaum, Hillsdale, NJ, 1989. 137. I. Aleksander, ed., Neural Computing Architectures, MIT Press, Cambridge, MA, 1989. 138. S. J. Hanson and C. R. Olson, eds, Connectionist Modeling and Bruin Function-The Developing btterface, MIT Press, Cambridge, MA, 1989. 139. L. Nadel, ed., Neural Connections, Mental Computation, MIT Press, Cambridge, MA, 1989. 140. C. C. Klimasauskas, The 1989 Neuro-Computing Bibliography, MIT Press, Cambridge, MA, 1989. 141. R. Pfeifer, Z. Schreter, F. Fogelman-Soulie, and L. Steels, eds., Connectionism in Perspective, North-Holland, Amsterdam, 1989. 142. P. Wasserman, Neural Computing-Theory and Applications, Van Nostrand, New York, 1989. 143. S. Brunak and B. Lautrup, Neural Networks-Computers with Intuition, World Scientific, Singapore, 1989.
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144. B. Lautrup, The Hopjield Model, World Scientific, Singapore, 1989. 145. C. A. Will, ed., The Neural Network Review, Erlbaum, 1987ff. 146. H. Szu, ed., Journal of Neural Network Computing-Technology, Design, and Applications. Auerbach, 1989ff. 147. B. Lautrup and S. BNIK&, eds., International Journal of Neural Systems, World Scientific, 1989ff. in Neural Systems, American Institute of Physics, 148. D. J. Amit, ed., NETWORK-Computation 199off.
149. G. Buchsbaum and W. Freedman, guest eds., Special Issue on Neurosystems and Neuroengineering, IEEE Trans. Biomedical Engineeting 36 cl), January 1989, 2-160. 150. M. A. Arbib, guest ed., Special Issue: Neural Computing, JPDC 6 (21, April 1989, 183-449. 151. G. E. Hinton, Connectionist learning procedures, AI 40, 1989, 185-234. 152. H. J. Caulfield, J. Kinser, and S. K. Rogers, Optical neural networks, P-IEEE 77, 1989, 1573-1583. 153. E. Saund, Dimensionality-reduction using connectionist networks, T-PAMI 11, 1989, 304-314. 154. D. Haussler and L. Pitt, eds., Proceedings of the 1988 Workshop on Computational Learning Theory, Morgan Kaufmann, San Mateo, CA, 1988. 155. R. Forsyth, ed., Machine Learning--Principles and Techniques, Chapman and Hall, New York, 1989.
156. J. G. Carbonell, guest ed., Special Volume on Machine Learning, AI 40 (l-3), September 1989, l-385.
B.8. Pattern Recognition,
Artificial
Intelligence
157. N. G. Zagoruiko, guest ed., Proceedings of the International Workshop on Expert Systems and Pattern Recognition (ESPR) (Novosibirsk, USSR, October 26-29, 1987), IJPRAI 3 (1). March 1989, 1-157. 158. G. Ferrate et al., eds., Syntactic and Structural Pattern Recognition, Springer, Berlin, 1988. 159. J. Kittler, ed., Pattern Recognition, Springer, Berlin, 1988. 160. T. O’Shea and V. Sgurev, eds., Artificial Intelligence III-Methodology, Systems, Applications (Proceedings of the Third International Conference, AIMSA ‘88, Varna, Bulgaria, September 20-23, 19881,North-Holland, Amsterdam, 1988. 161. Fifth IEEE Conference on Artificial Intelligence Applications, Miami, FL, March 6-10, 1989. 162. M. M. Trivedi, ed., Applications of Artificial Intelligence VII (Orlando, FL, March 28-30, 1989). Proc. SPIE 1095.
163. IJCAI’89, Eleventh International Joint Conference on Artificial Intelligence, Detroit, MI, August 20-25, 1989.
164. A. G. Cohn, ed., AISB’89, Morgan Kaufmann, San Mateo, CA, 1989 165. M. Pavel, Fundamentals of Pattern Recognition, Dekker, New York, 1988. 166. C. W. Therrien, Decision Estimation and Classification-An Introduction to Pattern Recognition and Related Topics, Wiley, New York, 1989. 167. S. R. Graubard, ed., The Artijicial Intelligence Debate, MIT Press, Cambridge, MA, 1988. 168. M. Sharples, D. Hogg, C. Hutchison, S. Torrance, and D. Young, eds., Computers and Thought-A Practical Introduction to Artificial Intelligence, MIT Press, Cambridge, MA, 1989. 169. D. W. Bouldin, guest ed., Special Section on Advanced Systems Architectures for Artificial Intelligence, T-SMC 19 (4), July-August 1989, 665-713. 170. M. J. Swain, Comments on Samal and Henderson: “Parallel consistent labeling algorithms,” Intl. J. Parallel Programming 17, 1988, 523-528. 171. J. Kittler and E. R. Hancock, Combining evidence in probabilistic relaxation, IJPRAI 3, 1989, 29-51.
172. R. Bodington, G. D. Sullivan, and K. D. Baker, Consistent labelling of image features using an assumption-based truth maintenance system, n/C 7, 1989, 43-49. 173. J. S. Duncan and W. Frei, Relaxation labeling using continuous label sets, PRL 9, 1989, 27-37. 174. P. Parent and S. W. Zucker, Radial projection: an efficient update rule for relaxation labeling, T-PAMI 11, 1989, 886-889.
175. X. Zhuang, R. M. Haralick, and H. Joo, A simplex-like algorithm for the relaxation labeling process, T-PAMI 11, 1989, 1316-1321. 176. M. J. Swain and P. R. Cooper, Parallel hardware for constraint satisfaction, AAAI, 682-686.
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C. Applications C.1. Document
Processing
177. G. P. Herring and V. A. Uzilevsky, eds., International Journal of Research and Engineering-Postal Applications, 1989tf. 178. R. Suchenwirth, J. Guo, I. Hartmann, G. Hincha, M. Krause, and Z. Zhang, Optical Recognition of Chinese Characters, Vieweg, Berlin, 1989.
C.2. Biomedical Applications 179. V. L. Newhouse, ed., Progress in Medical Imaging, Springer, Berlin, 1988. 180. M. A. Viergever and A. Todd-Pokropek, eds., Mathematics and Computer Science in Medical Imaging, Springer, Berlin, 1988. 181. S. J. Dwyer III, R. G. Jost, and R. H. Schneider, eds., Medical Imaging III (Newport Beach, CA, 1989): Image Formation (January 29-311, Proc. SPZE 1090, Image Capture and Display (January 29-31), Proc. SPZE 1090, Image Processing (January 31-February 3), Proc. SPIE 1092; PACS System Design and Evaluation (January 31-February 3), Proc. SPZE 1093. 182. M. A. Viergever, ed., Science and Engineering of Medical Imaging (Paris, France, April 24-28, 19891, Proc. SPIE 1137. 183. R. A. Bauman, ed., Journal of Digital Imaging (Society for Computer Applications in Radiology), Saunders, 1988ff.
C.3. Industrial
Applications
184. H. Freeman, ed., Machine Vision for Inspection and Measurement (Second Annual Machine Vision Workshop, New Brunswick, NJ, April 25-26, 19881,Academic Press, Orlando, FL, 1989. 185. Third Annual Machine Vision Workshop, New Brunswick, NJ, April 3-4, 1989. 186. IEEE International Workshop on Industrial Applications of Machine Intelligence and Vision (MIV-891, Tokyo, Japan, April 10-12, 1989. 187. Vision ‘89 (Society of Manufacturing Engineers), Rosemont, IL, April 24-27, 1989. 188. Ident/Vision (2nd International Conference on Applied Vision and Artificial Intelligence and 3rd International Conference on Automatic Identification and Sensors); ROVISEC (8th International Conference on Robot Vision and Sensory Control); AIPC (9th International Conference on Automated Inspection and Product Control), Stuttgart, FRG, May 30-June 1, 1989. 189. D. J. Svetkoff, ed., Optics, Illumination, and Sensing for Machine Vision (Philadelphia, PA, November 8-10, 19891, Proc. SPIE 1194. 190. M. J. W .Chen, ed., Automated Inspection and High Speed Vision Architectures (Philadelphia, PA, November 6-7, 19891, Proc. SPIE 1197. 191. J. L. C. Sanz, Advances in Machine Vision, Springer, Berlin, 1988. 192. L. F. Pau, Computer Vision for Electronics Manufacturing, Plenum, New York, 1989. 193. J. Encarnacao and U. Rembold, guest eds., Graphics for Robotics and CAD/CAM/CIM Planning, CGA 9 (11, January 1989, 14-74. 194. C. T. Wilfong, guest ed., Robotics and Automation, Computer 22 (31, March 1989, 6-60. 195. A. J. Koivo, W. A. Gruver, C. P. Neuman, H. E. Stephanou, and L. W. Stark, eds., Special Section on Information Technology for Sensory-Based Robot Manipulators, T-SMC 19 (4), July-August, 1989, 780-860. 196. A. Kusiak, ed., Journal of Intelligent Manufacturing, Chapman and Hall, 199Off. 197. G. Rodriguez, ed., Intelligent Control and Adaptive Systems (Philadelphia, PA, November 7-8, 19891, Proc. SPZE 1196. 198. 0. Khatib, J. J. Craig, and T. Lozano-Perez, eds., The Robotics Review I MIT Press, Cambridge, MA, 1989. 199. J. M. Brady, ed., Special Issue on Sensor Data Fusion, ZJRR 7 (61, December 1988, 1-161. 200. V. J. Lumelsky and R. A. Brooks, eds., Special Issue on Sensor-Based Planning and Control in Robotics, T-JU 5 (61, December 1989, 713-825.
C.4. Autonomous
Systems
201. A. G. Gale, M. H. Freeman, C. M. Haslegrave, P. Smith, and S. P. Taylor, eds., Vision in Vehicles 11 (Nottingham, UK, September 14-17, 19871,North-Holland, Amsterdam, 1988. 202. Mini-Symposium on Robot Navigation, Stanford, CA, March 28-30, 1989.
IMAGE ANALYSIS AND COMPUTER
VISION: 1989
199
203. International Workshop on Visual Information Processing for Television and Telerobotics. Williamsburg, VA, May 10-12, 1989. 204. SITEF 89, Research Trends and Application Impacts of Machine and Systems Intelligence. Tolouse, France, October 18-19, 1989. 205. W. J. Wolfe, ed., Mobile Robots IV (Philadelphia, PA, November 6-7, 19891, Proc. SPIE 1195. 206. International Conference on Intelligent Autonomous Systems, Amsterdam, The Netherlands. December 11-14, 1989. 207. S. S. Iyengar and R. L. Kashyap, guest eds., Autonomous Intelligent Machines, Computer 22 (6). June 1989, 14-97. 208. J. Bares, M. Hebert, T. Kanade, E. Krotkov, T. Mitchell, R. Simmons, and W. Whittaker. Ambler -an autonomous rover for planetary exploration, Computer 22 (61, 1989, 18-26. 209. C. R. Weisbin, G. de Saussure, J. R. Einstein, F. G. Pin, and E. Heer. Autonomous mobile robot navigation and learning, Computer 22 (6), 1989, 29-3.5. 210. N. S. V. Rao, Algorithmic framework for learned robot navigation in unknown terrains, Compute! 22 (6), 1980, 37-43. 211. A. M. Flynn, Combining sonar and infrared sensors for mobile robot navigation, IJRR 7 (6). 1988. 5-14. 212. U. K. Sharma and D. Kuan, Real-time model based geometric reasoning for vision-guided navigation, MVA 2, 1989, 31-44. 213. D. J. Kriegman, E. Triendl, and T. 0. Binford, Stereo vision and navigation in buildings for mobile robots, T-RA 5, 1989, 792-804. 214. D. T. Lawton and T. S. Levitt, Knowledge based vision for terrestrial robots, IUW, 128-133. 215. K. E. Olin, M. J. Daily, J. G. Harris, and F. M. Vilnrotter, Knowledge-based vision technology overview for obstacle detection and avoidance, IUW, 134-143. 216. C. Fennema, A. Hanson, and E. Riseman, Towards autonomous mobile robot navigation, IUW. 219-231. 217. C. Thorpe and T. Kanade, Carnegie Mellon Navlab Vision, IUW, 273-282. 218. D. P. Miller, R. Brooks, R. Chatila, S. Harmon, S. Rosenschein, C. Thorpe, and C. Weisbin. Robot navigation, IJCAI, 1672-1674. 219. J. J. Rodriguez and J. K. Aggarwal, Navigation using image sequence analysis and 3-D terrain matching, WISDS, 200-207.
C.5. Remote Sensing, Reconnaissance 220. I. Hirschberg, ed., Reconnaissance, Astronomy, Remote Sensing, and Photogrammetry (Lox Angeles, CA, January 19-20, 19891,Proc. SPZE 1070. 221. 0. E. Drummond, ed., Digital Signal Processing, Association and Tracking of Point Source. Small and Cluster Targets (Orlando, FL, March 27-29, 1989), Proc. SPZE 1096. 222. M. R. Weathersby, ed., Aerospace Pattern Recognition (Orlando, FL, March 30-31, 1989), Proc. SPIE 1098.
223. A. G. Tescher, ed., Advances in Image Compression and Automatic Target Recognition (Orlando. FL, March 30-31, 1989), Proc. SPZE 1099. 224. C. Weaver, ed., Sensor Fusion II (Orlando, FL, March 28-29, 1989), Proc. SPZE 1100. 225. A. J. Huber, ed., Imaging Infrared: Scene Simulation and Real Image Tracking (Orlando, FL, March 30-31, 1989), Proc. SPZE 1110. 226. G. Duchossois, F. L. Herr, and R. Zander, eds., Advanced Optical Instrumentation for Remote Sensing of the Earth’s Surface from Space (Paris, France, April 24-28, 1989), Proc. SPIE 1129. 227. P. A. Hendel, F. R. LaGesse, W. W. Schurter, T. W. Augustyn and T. G. Shepherd, eds., Airborne Reconnaissance XIII (San Diego, CA, August 7-9, 1989), Proc. SPIE 1156. 228. D. M. McKeown, Jr., W. A. Harvey, and L. E. Wixson, Automating knowledge acquisition for aerial image interpretation, CVGZP 46, 1989, 37-81. 229. W. W. SeemuIIer, The extraction of ordered vector drainage networks from elevation data. CVGIP 47, 1989, 48-58.
230. M. G. Thomason, Knowledge-based analysis of satellite oceanographic images, Id. J. Intelligenf Systems 4, 1989, 143-154. 231. D. C. Baker, S. S. Hwang, and J. K. Aggarwal, Detection and segmentation of man-made objects in outdoor scenes: concrete bridges, JOSA A6, 1989, 938-950.
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ROSENFELD
232. V. Roberto and A. Peron, Low-level processing techniques in geophysical image interpretation, PRL 10, 1989, 111-122. 233. M. E. Bernard, Detection of airborne compact sources in infra-red scenes using syntactic pattern recognition, PRL. 10, 1989, 123-126. 234. B. Bhanu, Understanding scene dynamics, IUW, 147-164. 235. G. .I. Ettinger and T. S. Levitt, An intelligent tactical target screener, IUW, 283-297. 236. J. F. Bogdanowicz and A. Newman, Overview of the SCORPIUS program, IUW, 298-308. 237. D. E. Dudgeon, J. G. Verly, and R. L. Delaney, An experimental target recognition system for laser radar imagery, IUW, 479-506. 238. P. Fua and A. J. Hanson, Objective functions for feature discrimination: applications to semiautomated and automated feature extraction, IUW, 676-694. 239. M. A. Fischler and T. M. Strat, Recognizing objects in a natural environment: a contextual vision system (CVC), IUW, 774-796. 240. K. Kaneda, F. Kato, E. Nakamae, T. Nishita, H. Tanaka, and T. Noguchi, Three-dimensional terrain modeling and display for environmental assessment, SIGGRAPH, 207-214. 241. A. Huertas, W. Cole, and R. Nevatia, Using generic knowledge in analysis of aerial scenes: a case study, IJCAI, 1642-1648.
C.6. Other Applications 242. H. T. A. Whiting, ed., Human Movement Science, North-Holland, 1982ff. 243. A. W. Young and H. D. Ellis, eds., Handbook of Research on Face Processing, North-Holland, Amsterdam, 1989.
D. Architectures D. 1. General References 244. M. Cosnard, M. H. Barton, and M. Vanneschi, eds., Parallel Processing (IFIP Working Group, Pisa, Italy, April 25-27, 1988), North-Holland, Amsterdam, 1988. 245. W. E. Nagel, 1988 International Conference on Supercomputing, PC 9, 1988-9, 117-118. 246. J. F. Hake and R. J. Van der Pas, The 2nd International Conference on Vector and Parallel Computing: Issues in Applied Research and Development, PC 9, 1988-9, 119-122. 247. R. Mills, ed., Proceedings, The 2nd Symposium on the Frontiers of Massively Parallel Computation (Fairfax, VA, October 10-12, 1988), Computer Society Press, Washington, DC, 1988. 248. International Conference on Systolic Arrays, Killamey, Ireland, May 31-June 2, 1989. 249. ACM Symposium on Parallel Algorithms and Architectures, Santa Fe, NM, June 18-21, 1989. 250. International Conference on Parallel Processing, St. Charles, IL, August 8-12, 1989. 251. Parallel Computing 89, Leiden, The Netherlands, August 29-September 1, 1989. 252. C. R. Dyer, ed., Special Section on Computer Architectures and Parallel Algorithms for PAM1 (Papers presented at the Workshop on Computer Architecture for Pattern Analysis and Machine Intelligence, Seattle, WA, October 5-7, 1987), T-PAMI 11 (3), March 1989, 225-265. 253. J. L. C. Sanz, ed., Position papers presented at the panel: Which parallel architectures are useful/useless for vision algorithms, WA 2, 1989, 167-173. 254. D. Gannon, A. Lichewsky, Y. Muraoka, and A. Sameh, eds., International Journal of High Speed Computing, World Scientific, 1989tI. 255. S. G. Akl, The Design and Analysis of Parallel Algorithms, Prentice-Hall, Englewood Cliffs, NJ, 1989. 256. K. Preston, Jr., The Abingdon Cross benchmark survey, Computer 22 (71, 1989, 9-18. 257. C. Weems, E. Riseman, A. Hanson, and A. Rosenfeld, A report on the results of the DARPA Integrated Image Understanding Benchmark Exercise, IUW, 165-192.
0.2.
Meshes, Hypercubes, etc.
258. H. Simon, ed., Scientific Applications of the Connection Machine (Mountainview, CA, September 12-14, 19881,World Scientific, Singapore, 1989. 259. S. Ranka and S. Sahni, Hypercube Algotithms for Image Processing and Pattern Recognition, Springer, Berlin, 1989. 260. W. D. Gropp and I. C. F. Ipsen, Recursive mesh refinement on hypercubes, BIT 29, 1989, 186-211.
IMAGE ANALYSIS AND COMPUTER
VISION: 1989
201
261. F. Ozguner and C. Aykanat, A reconfiguration algorithm for fault tolerance in a hypercube multiprocessor, IPL 29, 1988, 247-254. 262. A. M. Gibbons and Y. N. Srikant, A class of problems efficiently solvable on mesh-connected computers including dynamic expression evaluation, IPL 32, 1989, 305-311. 263. V. Di Gesu, An overview of pyramid machines for image processing, IS 47, 1989, 17-34. 264. I. D. Scherson, S. Sen, and Y. Ma, Two nearly optimal sorting algorithms for mesh-connected processor arrays using shear-sort, JPDC 6, 1989, 1.51-16.5. 265. T. Bier and K. F. Lee, Embedding of binary trees into hypercubes, JPDC 6, 1989, 679-691. 266. A. Wagner, Embedding arbitrary binary trees in a hypercube, JPDC 7, 1989, 503-520. 267. L. Boxer and R. Miller, Dynamic computational geometry on meshes and hypercubes. J. Supercomputing 3, 1989, 161-191. 268. J. P. Sheu, C. L. Wu, and G. H. Chen, Selection of the first k largest processes in hypercubes. PC 11, 1989, 381-384. 269. M. S. Chen and K. G. Shin, On relaxed squashed embedding of graphs into a hypercube, SIAM JC 18, 1989, 1226-1244. 270. I. D. Scherson and S. Sen, Parallel sorting in two-dimensional VLSI models of computation, T-COMP 38, 1989, 238-249. 271. R. Miller and Q. F. Stout, Mesh computer algorithms for computational geometry, T-COMP 38, 1989, 321-340. 272. H. G. Badr and S. Podar, An optimal shortest-path routing policy for network computers with regular mesh-connected topologies, T-COMP 38, 1989, 1362-1371. 273. G. E. Blelloch, Scans a primitive parallel operations, T-COMP 38, 1989, 1.520-1538. 274. J. J. Little, G. E. BIelIoch, and T. A. Cass, Algorithmic techniques for computer vision on a fine-grained parallel machine, T-PAMI 11, 1989, 244-257. 275. V. K. Prasanna-Kumar and D. I. Reisis, Image computations on meshes with multiple broadcast. T-PAMI 11, 1989, 1194-1202.
0.3.
Other Systems
276. R. Bakalash and A. Kaufman, Medicube: a 3D medical imaging architecture, C&G 13, 1989. 151-157. 277. H. Umeo and T. Asano, Systolic algorithms for computational geometry problems-a survey, Computing 41, 1989, 19-40. 278. L. S. Dreschler-Fischer and H. Faasch, A kernel system for iconic image processing, Comprdting 42, 1989, 91-108. 279. L. G. C. Hamey, J. A. Webb, and I. C. Wu, An architecture independent programming language for low-level vision, CVGIP 48, 1989, 246-264. 280. R. S. Wallace, J. A. Webb, and I. C. Wu, Machine-independent image processing: performance of Apply on diverse architectures, CVGIP 48, 1989, 265-276. 281. C. C. Weems, S. P. Levitan, A. R. Hanson, and E. M. Riseman, The Image Understanding Architecture, N W 2, 1989, 251-282. 282. 0. H. Ibarra and T. Jiang. Optimal simulation of tree arrays by linear arrays, IPL 30, 1989. 295-302. 283. P. W. Pachowicz, Image processing by software parallel computation, W C 7, 1989, 122-128. 284. A. W. G. Duller, R. H. Storer, A. R. Thomson, and E. L. Dagless, An associative processor array for image processing, IVC 7, 1989, 151-158. 285. 0. H. Ibarra, T. Jiang, and J. H. Chang, On iterative and cellular tree arrays, JCSS 38, 1989. 452-473. 286. C. H. Chu, E. J. Delp, L. H. Jamieson, H. J. Siegel, and F. J. Weil, A model for an intelligent operation system for executing image understanding tasks on a reconfigurable parallel architecture, JPDC 6, 1989, 598-622. 287. A. Rosenfeld, Arc colorings, partial path groups, and parallel graph contractions, JPDC 7, 1989. 335-354. 288. M. Maresca, H. Li, and M. M. C. Sheng, Parallel computer vision on polymorphic torus architecture, W A 2, 1989, 215-230. 289. E. H. L. Aarts and J. H. M. Korst, Computations in massively parallel networks based on the Boltzmann machine: a review, PC 9, 1988-9, 129-145.
202
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290. H. M. Alnuweiri and V. K. Prasanna-Kumar, An efficient VLSI architecture with applications to geometric problems, PC 12, 1989, 71-93. 291: T. Saito and H. Nishio, Structural and behavioral equivalence relations in automata networks, TCS 63, 1989, 223-237. 292. C. J. Zarowski, R. D. McLeod, and H. C. Card, Primitive cellular automata, threshold decomposition, and ranked order operations, T-CUMZ’ 38, 1989, 148-149. 293. R. S. Wallace and M. D. Howard, HBA vision architecture: built and benchmarked, T-PAMZ 11, 1989, 227-232. 294. H. Li and M. Maresca, Polymorphic-torus architecture for computer vision, T-PAMZ 11, 1989, 233-243. 295. W. Yang and A. M. Chiang, VLSI processor architectures for computer vision, IUW, 193-199. 296. J. A. Webb and M. B. MacPherson, The second DARPA Image Understanding Benchmark on Warp and extending Apply to include global operations, IUW, 597-616. 297. P. Kahn, D. Disabatino, and D. T. Lawton, MAC-II based IU environment development, IUW, 640-650. 298. K. Kim and V. K. Prasanna Kumar, Parallel memory systems for image processing, CVPR, 6.54-659. 299. D. Rhoden and C. Wilcox, Hardware acceleration for window systems, SIGGRAPH, 61-68. 300. M. Potmesil and E. M. Hoffert, The Pixel Machine: a parallel image computer, SIGGRAPH, 69-78. 301. H. Fuchs, J. Poulton, J. Eyles, T. Greer, J. Goldfeather, D. Ellsworth, S. Molnar, G. Turk, B. Tebbs, and L. Israel, Pixel-Planes 5: a heterogeneous multiprocessor graphics system using processor-enhanced memories, SIGGRAPH, 79-88.
0.4. Related Topics 302. T. L. Kunii, ed., Visual Database Systems (IFIP Working Conference, Tokyo, Japan, April 3-7, 19891, North-Holland, Amsterdam, 1989. 303. Symposium on the Design and Implementation of Large Spatial Databases, Santa Barbara, CA, July 17-18, 1989. 304. IEEE Workshop on Visual Languages, Rome, Italy, October 4-6, 1989. 305. E. A. Fox, guest ed., Special Section on Interactive Technology, Comm. ACM 32 (7), July 1989, 794-889. 306. W. I. Grosky and R. Mehrotra, guest eds., Image Database Management, Computer 22 (12), December 1989, 7-71. 307. G. C. Roman and K. C. Cox, A declarative approach to visualizing concurrent computations, Computer 22 (101, 1989, 25-36. 308. A. M. Goodman, R. M. Haralick, and L. G. Shapiro, Knowledge-based computer visionintegrated programming language and data management system design, Computer 22 (121, 1989, 43-54. 309. A. Pizano, A. Klinger, and A. Cardenas, Specification of spatial integrity constraints in pictorial database, Computer 22 (121, 1989, 59-71.
E. Computational Techniques E .1. Image Operations 310. J. Serra, guest ed., Special Issue on Advances in Mathematical Morphology, SP 16 (41, April 1989, 297-431. 311. K. S. Huang, Binary image algebra and optical cellular logic processor design, CVGZP 45, 1989, 295-345. 312. J. M. Rebordao, Lookup table loadings for image processing with controlled knots, CVGZP 47, 1989, 189-202. 313. G. E. Sotak, Jr. and K. L. Boyer, The Laplacian-of-Gaussian kernel: a formal analysis and design procedure for fast, accurate convolution and full-frame output, CVGZP 48, 1989, 147-189. 314. R. C. Staunton, The design of hexagonal sampling structures for image digitization and their use with local operators, TVC 7, 1989, 162-166. 315. P. J. Besl, J. B. Birch, and L. T. Watson, Robust window operators, MVA 2, 1989, 179-191.
IMAGE ANALYSIS AND COMPUTER
VISION:
1989
203
316. L. Ji, J. Piper, and J. Y. Tang, Erosion and dilation of binary images by arbitrary structuring elements using interval coding, PRL 9, 1989, 201-209. 317. A. Rosenfeld and J. M. Jolion, Local operations on labelled dot patterns, PRL 9, 1989, 225-232. 318. F. Meyer and J. Serra, Contrasts and activity lattice, S P 16, 1989, 303-317. 319. L. Vincent, Graphs and mathematical morphology, S P 16, 1989, 365-388. 320. M. Schmitt, Mathematical morphology and artificial intelligence: an automatic programming system, S P 16,1989,389-401. 321. J. P. F. D’Haeyer, Gaussian filtering of images: a regularization approach, S P 18, 1989, 169-181. 322. M. A. Sid-Ahmed, A systolic realization for 2-D digital filters, T-ASP 37, 1989, 560-565. 323. Z. Fang, X. Li, and L. M. Ni, On the communication complexity of generalized 2-D convolution on array processors, T-COMP 38, 1989, 184-194. 324. F. Y. C. Shih and 0. R. Mitchell, Threshold decomposition of gray-scale morphology into binary morphology, T-PAMI 11, 1989, 31-42. 325. P. Maragos, A representation theory for morphological image and signal processing, T-PAMI 11, 1989,586-599.
326. G. E. Sotak, Jr. and K. L. Boyer, Comments on “Fast convolution with Laplacian-of-Gaussian masks,” T-PAMZ 11, 1989, 1329-1332. 327. J. Xu, The optimal implementation of morphological operations on neighborhood connected array processors, CVPR, 166-171. 328. E. R. Dougherty, The dual representation of gray-scale morphological filters, CVPR, 172-177.
E.2. Multiresolution
and Scale Space Methods
329. S. L. Tanimoto, ed., Special Section on Multiresolution Representation, T-PAM1 11 (71, July 1989, 673-748. 330. P. Meer, Stochastic image pyramids, CVGIP 45, 1989, 269-294. 331. C. L. Tan and W. N. Martin, An analysis of a distributed multiresolution vision system, PR 22, 1989, 257-265. 332. N. G. Bourbakis and A. Klinger, A hierarchical picture coding scheme, PR 22. 1989, 317-329. 333. A. Toet, Image fusion by a ratio of low-pass pyramid, PRL. 9, 1989, 245-253. 334. A. Toet, A morphological pyramidal image decomposition, PRL 9, 1989, 255-261. 335. J. B. D. S. Martens and G. M. M. Majoor, The perceptual relevance of scale-space image coding, S P 17, 1989, 353-364.
336. B. Gidas, A renormalization group approach to image processing problems, T-PAM1 11, 1989, 164-180.
337. S. G. Mallat, A theory for multiresolution signal decomposition: the wavelet representation, T-PAMI 11, 1989, 674-693.
338. M. H. Chen and P. F. Yan, A multiscaling approach based on morphological filtering, T-PAM1 11, 1989, 694-700.
339. P. Maragos, Pattern spectrum and multiscale shape representation, T-PAMZ 11, 1989, 701-716. 340. S. Peleg, M. Werman, and H. Rom, A unified approach to the change of resolution: space and gray-level, T-PAM1 11, 1989, 739-742. 341. J. J. Koenderink, A hitherto unnoticed singularity of scale-space, T-PAMI 11, 1989, 1222-1224. 342. P. Meer, C. A. Sher, and A. Rosenfeld, Processing of line drawings in a hierarchical environment, CVPR, 638-645.
E.3. Geometric Transformations,
Calibration
343. D. Fraser, Comparison at high spatial frequencies of two-pass and one-pass geometric transformation algorithms, CVGZP 46, 1989, 267-283. 344. R. Horaud, B. Conio, 0. Leboulleux, and B. Lacolle, An analytic solution for the perspective 4-point problem, CVGIP 47, 1989, 33-44. 345. A. Goshtasby, Correction of image deformation from lens distortion using Bezier patches, CVGIP 47, 1989,385-394. 346. Z. Chen, D. C. Tseng, and J. Y. Lin, A simple vision algorithm for 3-D position determination using a single calibration object, PR 22, 1989, 173-187.
347. R. M. Haralick, Determining camera parameters from the perspective projection of a rectangle, PR 22,1989,223-230.
348. L. Lalitha and D. Dutta Majumder, Fractal based criteria to evaluate the performance of digital image magnification techniques, PRL. 9, 1989, 67-75.
204
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349. R. K. Lenz and R. Y. Tsai, Calibrating a Cartesian robot with eye-on-hand configuration independent of eye-to-hand relationship, T-PAMZ 11, 1989, 916-928. 350. E. L. Schwartz, A. Shaw, and E. Wolfson, A numerical solution to the generalized mapmaker’s problem: flattening nonconvex polyhedral surfaces, T-PAMZ 11, 1989, 1005-1008. 351. Y. C. Shiu and S. Ahmad, Calibration of wrist-mounted robotic sensors by solving homogeneous transform equations of the form Rx = XB, T-Z?,4 5, 1989, 16-29. 3.52. J. S. C. Yuan, A general photogrammetric method for determining object position and orientation, T-RA 5, 1989, 129-142. 353. R. Y. Tsai and R. K. Lenz, A new technique for fully autonomous and efficient 3D robotics hand/eye calibration, T-RA 5, 1989, 345-358. 354. G. Wolberg, Skeleton-based image warping, 1/% 5, 1989, 95-108. 355. Z. Zhuang and 0. D. Faugeras, Calibration of a mobile robot with application to visual navigation, WVM, 306-313. 356. R. Kumar, Determination of camera location and orientation, IUW, 870-881. 357. R. Horaud, B. Conio, 0. Leboulleux, and B. Lacolle, An analytic solution for the perspective 4-point problem, CVPR, 500-507. 358. J. K. Kearney, X. Yang, and S. Zhang, Camera calibration using geometric constraints, CVPR, 672-679. 359. M. Gangnet, J. C. Herve, T. Pudet, and J. M. Van Thong, Incremental computation of planar maps, SIGGRAPH, 345-354. 360. G. Wolberg and T. E. Boult, Separable image warping with spatial lookup tables, SIGGRAPH, 369-378. 361. R. Kumar and A. R. Hanson, Robust estimation of camera location and orientation from noisy data having outliers, WI3DS, 52-60. 362. Conference on Optical 3D Measurement Techniques, Vienna, Austria, September 18-20, 1989.
E.4. Interpolation, Function Fitting, etc. 363. R. Szeliski, &yes&r Modeling of Uncertainty in Low-Level Ksion, Kluwer, Boston, 1989. 364. E. Aarts and J. Korst, Simulated Annealing and Boltzmann Machines: A Stochastic Approach to Combinatorial Optimization and Neural Computing, Wiley, New York, 1989. 365. H. Imai, K. Kato, and P. Yamamoto, A linear-time algorithm for linear L, approximation of points, Algotithmica 4, 1989, 77-96. 366. A. L. Yuille, Energy functions for early vision and analog networks, BC 61, 1989, 115-123. 367. L. Piegl, A negative experiment with univariate blending functions, C& G 13, 1989, 217-222. 368. Y. Fletcher and D. F. McAllister, A tension-compatible patch for shape-preserving surface interpolation, CGA 9 (3), 1989, 45-55. 369. L. Piegl and W. Tiller, A menagerie of rational B-spline circles, CGA 9 (51, 1989, 48-56. 370. B. A. Barsky and T. DeRose, Geometric continuity of parametric curves: three equivalent characterizations, CGA 9 (61, 1989, 60-68. 371. N. Eichhorn and H. Kiesewetter, Integer analysis of two-dimensional polygonal objects, Computing 42, 1989, 1-16. 372. G. Walz, On interpolation by generalized planar splines I: The polynomial case, Computing 42, 1989, 187-194. 373. 0. Egecioglu, E. Gallopoulos, and C. K. Koc, Parallel Hermite interpolation: an algebraic approach, Computing 42, 1989, 291-307. 374. B. Pham, Conic B-splines for curve fitting: a unifying approach, CVGZP 45, 1989, 117-125. 375. M. Berman, Large sample bias in least squares estimators of a circular arc center and its radius, CVGZP 45, 1989, 126-128. 376. J. Y. Jou and A. C. Bovik, Improved initial approximation and intensity-guided discontinuity detection in visible-surface reconstruction, CVGZP 47, 1989, 292-326. 377. F. Cheng and A. Goshtasby, A parallel B-spline surface fitting algorithm, TOG 8, 1989, 41-50. 378. B. Joe, Multiple-knot and rational cubic Beta-splines, TOG 8, 1989, 100-120. 379. J. L. Mallet, Discrete smooth interpolation, TOG 8, 1989, 121-144. 380. J. Peters, Local generalized Hermite interpolation by quartic C2 space curves, TOG 8, 1989, 235-242. 381. H. Prautzsch, A round trip to B-splines via de Casteljau, TOG 8, 1989, 243-254. 382. X. Nie and R. Unbehauen, Efficient evaluation of 1-D and 2-D polynomials at equispaced points, T-ASSP 37, 1989, 1623-1626.
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205
383. A. Blake, Comparison of the efficiency of deterministic and stochastic algorithms for visual reconstruction, T-PAMI 11, 1989, 2-12. 385. C. H. Lee, Image surface approximation with irregular samples, T-PAM1 11. 1989, 206-212. 386. I. Weiss, Line fitting in a noisy image, T-PAM1 11, 1989, 325-329. 386. B. Shahraray and D. J. Anderson, Optimal estimation of contour properties by cross-validated regularization, T-PAMI 11, 1989, 600-610. 387. D. S. Chen, A data-driven intermediate level feature extraction algorithm, T-PAMI II, 1989. 749-758. 388. C. S. Fahn, J. F. Wang, and J. Y. Lee, An adaptive reduction procedure for the piecewise linear approximation of digitized curves, T-PAM1 11, 1989, 967-973. 389. B. Kamgar-Parsi, B. Kamgar-Parsi, and N. Netanyahu, A nonparametric method for fitting a straight line to a noisy image, T-PAMZ 11, 1989, 998-1001. 390. K. Harada and E. Nakamae, Sampling point setting on cubic splines for computer animation, VC 5, 1989, 14-21. 391. R. J. Low, Vector interpolation for surface normal calculation, VC 5, 1989, 158-159. 392. D. Geiger and F. Girosi, Mean field theory for surface reconstruction, IUW, 617-630. 393. D. Y. Kim. J. J. Kim, P. Meer, D. Mintz, and A. Rosenfeld, Robust computer vision: a least median of squares based approach, IUW, 1117-1134. 394. S. C. Liu and J. G. Harris, Generalized smoothing networks in early vision, CVPR, 184-191. 395. R. Szeliski, Fast surface interpolation using hierarchical basis functions, CVPR, 222-228. 396. S. S. Sinha and B. G. Schunck, Discontinuity preserving surface reconstruction, CVPR, 229-234. 397. C. L. Bajaj and I. Ihm, Hermite interpolation using real algebraic surfaces, CG, 94-103. 398. R. H. Bartels and R. T. Hardock, Curve-to-curve associations in spline-based inbetweening and sweeping, SIGGRAPH, 167-174. 399. R. L. Stevenson and E. J. Delp, Invariant reconstruction of visual surfaces, WDDS, 131-137. 400. J. L. Sanz, Multidimensional signal representation by zero crossings: an algebraic study, SIAM JC 49, 1989, 281-295. 401. K. M. Nashold and B. E. A. Saleh, Synthesis of two-dimensional binary images through band-limited systems: a slicing method, T-ASP 37, 1989, 1271-1279. 402. J. L. C. Sanz and T. T. Huang, Image representation by sign information, T-PAMI 11, 198’). 729-738.
F. Feature Detection, Segmentation, Image Ana&sis F.1. Feature Detection 403. N. K. Link and S. W. Zucker, Corner detection in curvilinear dot grouping. BC 59, 1988, 247-256. 404. L. J. van Vliet, I. T. Young, and G. L. Beckers, A nonlinear Laplace operator as edge detector in noisy images, CVGZP 45, 1989, 167-195. 405. B. Parvin and G. Medioni, Adaptive multiscale feature extraction from range data, CVGIP 45. 1989, 346-356. 406. L. J. Kitchen and J. A. Malin, The effect of spatial discretization on the magnitude and direction response of simple differential edge operators on a step edge, CVGIP 47, 1989, 243-258. 407. R. H. Park and W. Y. Choi, A new interpretation of the compass gradient edge operators. CVGIP 47, 1989, 259-265. 408. J. D. Cappelletti and A. Rosenfeld, Three-dimensional boundary following, CVGIP 48, 1989, 80-92. 409. K. Rangarajan, M. Shah, and D. Van Brackle, Optimal corner detector, CVGIP 48, 1989, 230-245. 410. P. L. Rosin and G. A. W. West, Segmentation of edges into lines and arcs, W C 7, 1989, 109-I 14. 411. J. M. Apffel, K. W. Current, J. L. C. Sanz, and A. K. Jain, An architecture for region boundary extraction in raster scan images suitable for VLSI implementation, M E A 2, 1989, 193-214. 412. M. H. Han, D. Jang, and J. Foster, Identification of cornerpoints of two-dimensional images using a line search method, PR 22, 1989, 13-20. 413. L. C. Topa and R. J. Schalkoff, Edge detection and thinning in time-varying image sequences using spatio-temporal templates, PR 22, 1989, 143-154. 414. P. Meer, S. Wang, and H. Wechsler, Edge detection by associative mapping, PR 22, 1989. 491-503.
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415. Y. S. Chen and W. H. Hsu, An interpretive model of line continuation in human visual perception, PR 22, 1989, 619-639. 416. J. Canning, J. J. Kim, N. Netanyahu, and A. Rosenfeld, Symbolic pixel labeling for curvilinear feature detection, PRL 8, 1988, 299-310. 417. A. Guiducci, Comer characterization by differential geometry techniques, PRL 8, 1988,311-318. 418. A. Premoli, P. Grattoni, and F. Pollastri, A non-sequential contour detection with a priori knowledge, PRL 9, 1989, 45-51. 419. R. Owens, S. Venkatesh, and J. Ross, Edge detection is a projection, PRL 9, 1989, 233-244. 420. B. B. Chaudhuri and B. U. Shankar, An efficient algorithm for extrema detection in digital images, PRL. 10, 1989,81-85. 421. M. Spann, C. Horne, and J. M. H. du Buf, The detection of thin structures in images, PRL. 10, 1989, 175-179.
422. M. Tanaka and T. Katayama, Edge detection and restoration of noisy images by the expectationmaximization algorithm, SP 17, 1989, 213-226. 423. J. J. Clark, Authenticating edges produced by zero-crossing algorithms, T-PAM1 11, 1989,43-57. 424. Y. T. Zhou, V. Venkateswar, and R. Chellappa, Edge detection and linear feature extraction using a 2-D random field model, T-PAMI 11, 1989, 84-95. 425. J. S. Chen, and G. Medioni, Detection, location, and estimation of edges, T-PAMI 11, 1989, 191-198. 426. Y. Lu and R. C. Jain, Behavior of edges in scale space, T-PAMI 11, 1989, 337-356. 427. P. Bouthemy, A maximum likelihood framework for determining moving edges, T-PAMZ 11, 1989,499-511.
428. P. Parent and S. W. Zucker, Trace inference, curvature consistency, and curve detection, T-PAMZ 11, 1989,823-839.
429. W. L. G. van Warmerdam and V. R. Algazi, Describing 1-D intensity transitions with Gaussian derivatives at the resolutions matching the transition widths, T-PAM1 11, 1989, 973-977. 430. E. De Micheli, B. Caprile, P. Ottonello, and V. Torre, Localization and noise in edge detection, T-PAMI 11, 1989, 1106-1117. 431. W. M. Krueger and K. Phillips, The geometry of differential operators with application to image processing, T-PAMZ 11, 1989, 1252-1264. 432. E. P. Lyvers, 0. R. Mitchell, M. L. Akey, and A. P. Reeves, Subpixel measurement using a moment-based edge operator, T-PAMZ 11, 1989, 1293-1309. 433. D. Lee, Edge detection, classification, and measurement, CVPR, 2-10. 434. A. Kundu, Robust edge detection, CVPR, 11-18. 435. J. S. Duncan and T. Birkholzer, Edge reinforcement using parameterized relaxation labeling, CVPR, 19-27. 436. 0. Monga and R. Deriche, 3D edge detection using recursive filtering: application to scanner images, CVPR, 28-35. 437. H. L. Tan, S. B. Gelfand, and E. J. Delp, A cost minimization approach to edge detection using simulated annealing, CVPR, 86-91. 438. A. M. M&or, Edge recognition in dynamic vision, CVPR, 118-123.
F.2. Segmentation 439. D. Blostein and N. Ahuja, A multiscale region detector, CVGIP 45, 1989, 22-41. 440. S. D. Yanowitz and A. M. Bruckstein, A new method for image segmentation, CVGIP 46, 1989, 82-95.
441. A. S. Abutaleb, Automatic thresholding of gray-level pictures using two-dimensional entropy, CVGIP 47, 1989, 22-32. 442. B. Kartikeyan and A. Sarkar, A unified approach for image segmentation using exact statistics, CVGZP 48, 1989, 217-229. 443. N. Ahuja and M. Tuceryan, Extraction of early perceptual structure in dot patterns: integrating region, boundary, and component Gestalt, CVGZP 48, 1989,304-356. 444. J. R. Beveridge, J. Griffith, R. R. Kohler, A. R. Hanson, and E. M. Riseman, Segmenting images using localized histograms and region merging, IJCV 2, 1989, 311-347. 445. Y. G. Leclerc, Constructing simple stable descriptions for image partitioning, ZJCV 3, 1989, 73-102. 446. D. H. Cooper, An object location strategy using shape and grey-level models, IVC 7, 1989, 50-56.
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207
447. B. J. Straub and W. E. Blanz, Combined decision theoretic and syntactic approach to image
segmentation, MVA 2, 1989, 17-30. 448. J. M. Jolion and A. Rosenfeld, Cluster detection in background noise, PR 22, 1989, 603-607. 449. S. Cho, R. Haralick, and S. Yi, Improvement of Kittler and Illingworth’s minimum error thresholding, PR 22, 1989, 609-617. 450. A. D. Brink, Grey-level thresholding of images using a correlation criterion, PRL. 9, 1989, 335-341. 451. J. M. Jolion and A. Rosenfeld, Coarse-fine bimodality analysis of circular histograms, PRL 10, 1989, 201-207. 452. N. R. Pal and S. K. Pal, Entropic thresholding, SP 16, 1989, 97-108. 453. J. M. Beaulieu and M. Goldberg, Hierarchy in picture segmentation: a stepwise optimization approach, T-PAMI 11, 1989, 150-163. 454. T. Bestul and L. S. Davis, On computing complete histograms of images in log(n) steps using hypercubes, T-PAM1 11, 1989, 212-213. 455. N. Yokoya and M. D. Levine, Range image segmentation based on differential geometry: a hybrid approach, T-PAM1 11, 1989, 643-649. 456. S. Lakshmanan and H. Derin, Simultaneous parameter estimation and segmentation of Gibbs random fields using simulated annealing, T-PAMI 11, 1989, 799-813. 457. Z. W. Bell, A Bayesian/Monte Carlo segmentation method for images dominated by Gaussian noise, T-PAM1 11, 1989, 985-990. 458. J. Goutsias and J. M. Mendel, Simultaneous optimal segmentation and model estimation of nonstationary noisy images, T-PAM1 11, 989, 990-998. 459. R. Mohan and R. Nevatia, Using perceptual organization to extract 3-D structures, T-PAMZ Il. 1989, 1121-1139. 460. J. S. Lee and M. C. K. Yang, Threshold selection using estimates from truncated normal distribution, T-SMC 19, 1989, 422-429. 461. A. K. C. Wong and P. K. Sahoo, A gray-level threshold selection method based on maximum entropy principle, T-SMC 19, 1989, 866-871. 462. E. Kawaguchi and R. I. Taniguchi, The depth first picture-expression as an image thresholding strategy, T-SMC 19, 1989, 1321-1328. 463. R. Mohan and R. Nevatia, Perceptual organization for segmentation and description, IIJW, 415-424. 464. P. Fua and A. J. Hanson, Objective functions for feature discrimination: theory, IUW, 443-460.
465. B. Bhanu, S. Lee, and J. Ming, Adaptive image segmentation using a genetic algorithm, IUW, 1043-1055. 466. Y. G. Leclerc, Image and boundary segmentation via minimal-length encoding on the Connection Machine, IUW, 1056-1069. 467. R. S. Wallace and T. Kanade, Finding hierarchical clusters by entropy minimization, IUW, 1105-1116. 468. J. Dolan and R. Weiss, Perceptual grouping of curved lines, IUW, 1135-1145. 469. E. Saund, Adding scale to the primal sketch, CVPR, 70-78. 470. L. H. Staib and J. S. Duncan, Parametrically deformable contour models, CVPR, 98-103. 471. R. Mohan and R. Nevatia, Segmentation and description based on perceptual organization, CVPR, 333-341. 472. A. Shio, An automatic thresholding algorithm based on an illumination-independent contrast measure, CVPR, 632-637. 473. P. Fua and A. J. Hanson, Objective functions for feature discrimination, IJCAI, 1596-1602. 474. E. P. D. Pednault, Some experiments in applying inductive inference principles to surface reconstruction, IJCAI, 1603-1609.
F.3. Image Analysis 475. J. Brolio, B. A. Draper, J. R. Beveridge, and A. R. Hanson, ISR: a database for symbolic processing in computer vision, Computer 22 (12), 1989, 22-30. 476. H. V. Jagadish and L. O’Gorman, An object model for image recognition, Computer 22 (12), 1989, 33-4 I. 477. N. Bartneck, A general data structure for image analysis, Computing 42, 1989. 17-34.
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478. T. Matsuyama, Expert systems for image processing: knowledge-based composition of image analysis processes, CI/GIP 48, 1989, 22-49. 479. B. A. Draper, R. T. Collins, J. Brolio, A. R. Hanson, and E. M. Riseman, The schema system, IJCV 2, 1989, 209-250. 480. V. V. Alexandrov and N. D. Gorsky, Expert systems simulating human visual perception, ZJPRAZ 3, 1989, 19-28. 481. S. N. Srihari and Z. Xiang, Spatial knowledge representation, ZJPRAZ 3, 1989, 67-84. 482. P. W. Woods, D. Pycock, and C. J. Taylor, A frame-based system for modelling and executing visual tasks, NC 7, 1989, 102-108. 483. S. Hopkins. G. J. Michaelson, and A. M. Wallace, Parallel imperative and functional approaches to visual scene labelling, ZPC 7, 1989, 178-193. 484. A. M. Wallace and P. McAndrew, Inferring the presence of objects from feature data, PRL 9, 1989, 287-295. 485. P. Bottom, P. Mussio, M. Protti, and R. Schettini, Knowledge-based contextual recognition and seiving of digital images, PRL 10, 1989, 101-110. 486. A. F. Bobick and R. C. Bolles, Representation space: an approach to the integration of visual information, II-W, 263-272. 487. T. S. Levitt, T. 0. Binford, G. J. Ettinger, and P. Gelband, Probability-based control for computer vision, IUW, 355-369. 488. W. Harvey, D. Kalp, M. Tambe, D. McKeown, and A. Newell, Measuring the effectiveness of task-level parallelism for high-level vision, II-W, 916-933. 489. S. Edelman and T. Poggio, Representations in high-level vision: reassessing the inverse optics paradigm, IUW, 944-949. 490. J. W. Modestino and J. Zhang, A Markov random field model-based approach to image interpretation, CVPR, 458-465. 491. A. F. Bobick and R. Bolles, Representation space: an approach to the integration of visual information, CVPR, 492-499. 492. J. Segen, Model learning and recognition of nonrigid objects, CVPR, 597-602. 493. V. Honavar and L. Uhr, Generation, local receptive fields and global convergence improve perceptual learning in connectionist networks, IJCAI, 180-185. 494. D. Kapur and J. Mundy, eds., Special Volume on Geometric Reasoning, AZ 37 (l-3), December 1988, 1-412. 495. D. Kapur and J. Mundy, eds., Geomehic Reasoning, MIT Press, Cambridge, MA, 1989. 496. D. Kapur and J. L. Mundy, Geometric reasoning and artificial intelligence: introduction to the special volume, AZ 37, 1988, l-11. 497. D. Kapur and J. L. Mundy, Wu’s method and its application to perspective viewing, AZ 37, 1988, 15-36. 498. D. S. Arnon, Geometric reasoning with logic and algebra, AZ 37, 1988, 37-60. 499. D. Kapur, A refutational approach to geometry theorem proving, AZ 37, 1988, 61-93. 500. H. P. Ko, Geometry theorem proving by decomposition of quasi-algebraic sets: an application of the Ritt-Wu principle, AZ 37, 1988, 95-122. 501. J. A. Goguen, Modular algebraic specification of some basic geometrical constructions, AZ 37, 1988, 123-153. 502. S. C. Chou and J. G. Yang, On the algebraic formulation of certain geometry statements and mechanical geometry theorem proving, Algorirhmica 4, 1989, 237-262. 503. D. Wang, On Wu’s method for proving constructive geometric theorems, IJCAI, 419-424. 504. M. Y. Kim, Visual reasoning in geometry theorem proving, IJCAI, 1617-1622. 505. R. B. Fisher and M. J. L. Orr, Experiments with a network-based geometric reasoning engine, IJCAI, 1623-1627. 506. M. Flasinski, Characteristics of edNLC-graph grammar for syntactic pattern recognition, CVGZP 47, 1989, 1-21. 507. A. Szepietowski, On three-way two-dimensional Turing machines, IS 47, 1989, 135-147. 508. J. Hromkovic, K. Inoue, and I. Takanami, Lower bounds for language recognition on two-dimensional alternating multihead machines, JCSS 38, 1989, 431-451. 509. A. Ito, K. Inoue, and I. Takanami, Deterministic two-dimensional on-line tessellation acceptors are equivalent to two-way two-dimensional alternating finite automata through 180 degree rotation, TCS 66, 1989, 273-287.
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209
510. U. Huckenbeck, Euclidean geometry in terms of automata theory, TCS 68, 1989, 71-87. 511. J. Clayson, Visual Modeling with LOGO-A Structured Approach to Seeing, MIT Press, Cambridge, MA, 1988. 512. H. Cohen, How to draw three people in a botanical garden, AAAI, 846-855.
G. Matching, G.l.
Stereo, and Time-Varying Imagery
Matching
513. C. Zetzsche and T. Caelli, Invariant pattern recognition using multiple filter image representations, CVGZP 45, 1989, 251-262. 514. R. Bajcsy and S. Kovacic, Multiresolution elastic matching, CVGIP 46, 1989, 1-21. 515. M. Herbin, A. Venot, J. Y. Devaux, E. Walter, J. F. Lebruchec, L. Dubertret, and J. C. Roucayrol, Automated registration of dissimilar images: application to medical imagery, CVGZP 47, 1989,77-88. 516. E. E. Milios, Shape matching using curvature processes, CVGIP 47, 1989, 203-226. 517. W. E. L. Grimson, On the recognition of parameterized 2D objects, IJCV 3, 1989, 353-372.
518. B. Yang, W. E. Snyder, and G. L. Bilbro, Matching oversegmented 3D images to models using association graphs, IVC 7, 1989, 135-143. 519. A. A. Amini, T. E. Weymouth, and D. J. Anderson, A parallel algorithm for determining two-dimensional object positions using incomplete information about their boundaries, PR 22, 1989, 21-28. 520. R. Sitaraman and A. Rosenfeld, Probabilistic analysis of two stage matching, PR 22, 1989, 331-343. 521. J. D. Tubbs, A note on binary template matching, PR 22, 1989, 359-365.
522. W. Wang, S. S. lyengar, and L. M. Patnaik, Memory-based reasoning approach for pattern recognition of binary images, PR 22, 1989,505-518. 523. Z. Jiang and W. Lu, A new digital image registration algorithm based on the double spatial intensity gradients using pyramids, PRL 8, 1988, 335-340. 524. T. G. Ryall and J. Sandor, Statistical pattern matching, PRL 9, 1989, 163-168. 525. P. Cox, H. Maitre, M. Minoux, and C. Ribeiro, Optimal matching of convex polygons, PRL 9, 1989,327-334. 526. H. Maitre and Y. Wu, A dynamic programming algorithm for elastic registration of distorted pictures based on autoregressive models, T-ASSP 37, 1989, 288-297. 527. S. S. Venkatesh and D. Psaltis, Binary filters for pattern classification, T-ASSP 37, 1989,604-611. 528. W. E. L. Grimson, On the recognition of curved objects, T-PAMI 11, 1989, 632-643.
529. V. K. Prasanna Kumar and V. Krishnan, Efficient parallel algorithms for image template matching on hypercube SIMD machines, T-PAM 11, 1989, 665-669. 530. R. Mehrotra and W. I. Grosky, Shape matching utilizing indexed hypothesis generation and testing, T-RA 5, 1989, 70-77. 531. T. C. Pong and B. G. Kaiser, A hierarchical approach to the correspondence problem, T-SMC 19,1989,271-276. 532. R. C. Nelson, Visual homing using an associative memory, IUW, 245-262.
533. F. P. Perlant and D. M. McKeown, Scene registration in aerial image analysis, IUW, 309-331. 534. J. R. Beveridge, R. Weiss, and E. M. Riseman, Optimization of 2-dimensional model matching, IUW, 815-830. 535. B. Kamgar-Parsi, J. L. Jones, and A. Rosenfeld, Registration of multiple overlapping range images: scenes without distinctive features, CVPR, 282-290. 536. D. B. Gennery, Visual terrain matching for a Mars rover, CVPR, 483-491. 537. J. K. Tsotsos, The complexity of perceptual search tasks, IJCAI, 1571-1577. 538. T. Risse, Hough transform for line recognition: complexity of evidence accumulation and cluster detection, CVGIP 46, 1989, 327-345. 539. H. K. Yuen, J. lllingworth, and J. Kittler, Detecting partially occluded ellipses using the Hough transform, n/C 7, 1989, 31-37. 540. D. Ben-Tzvi, A. A. Naqvi, and M. Sandler, Efficient parallel implementation of the Hough transform on a distributed memory system, NC 7, 1989, 167-172. 541. C. Guerra and S. Hambrusch, Parallel algorithms for line detection on a mesh, JPDC 6, 1989. l-19.
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542. E. R. Davies, Finding ellipses using the generalised Hough transform, PRL 9, 1989, 87-96. 543. E. R. Davies, Minimising the search space for polygon detection using the generalised Hough transform, PRL 9, 1989, 181-192. 544. J. M. Jolion and A. Rosenfeld, An O(log nl pyramid Hough transform, PRL 9, 1989, 343-349. 545. C. L. Huang, Elliptical feature extraction via an improved Hough transform, PRL 10, 1989, 93-100. 546. E. R. Davies, Occlusion analysis for object detection using the generalised Hough transform, SP 16, 1989, 267-277. 547. A. L. Fisher and P. T. Highnam, Computing the Hough transform on a scan line array processor, T-PAMI 11, 1989, 262-265. 548. I. D. Svalbe, Natural representations for straight lines and the Hough transform on discrete arrays, T-PAM1 11, 1989, 941-950. 549. A. Califano, Feature recognition using correlated information contained in multiple neighborhoods, AAAI, 831-836. 550. J. Princen, J. Illingworth, and J. Kittler, A hierarchical approach to line extraction, CVPR, 92-97. 551. A. Califano, R. M. Belle, and R. W. Taylor, Generalized neighborhoods: a new approach to complex parameter feature extraction, CVPR, 192-199. 552. P. M. Vaidya, Approximate minimum weight matching on points in k-dimensional space, Algotithmica 4, 1989, 569-583. 553. R. F. Zhu and T. Takaoka, A technique for two-dimensional pattern matching, Comm. ACM 32, 1989, 1110-1120. 554. J. S. Turner, Approximation algorithms for the shortest common superstring problem, IC 83, 1989, l-20. 555. C. Consel and 0. Danvy, Partial evaluation of pattern matching in strings, IPL 30, 1989, 79-86. 556. E. Makinen, On the subtree isomorphism problem for ordered trees, IPL 32, 1989, 271-273. 557. G. M. Landau and U. Vishkin, Fast parallel and serial approximate string matching, J. A1gotithm.s 10, 1989, 157-169. 558. P. M. Griffin, Correspondence of 2-D projections by bipartite matching, PRL 9, 1989, 361-366. 559. P. M. Vaidya, Geometry helps in matching, SZAMJC 18, 1989, 1201-1225. 560. K. Zhang and D. Shasha, Simple fast algorithms for the editing distance between trees and related problems, SOlMJC 18, 1989, 1245-1261. 561. T. Eilam-Tzoreff and U. Vishkin, Matching patterns in strings subject to multi-linear transformations, TCS 60, 1988, 231-254. 562. A. Mukherjee, Hardware algorithms for determining similarity between two strings, T-COMP 38, 1989, 600-603. 563. A. M. Landraud, J. F. Avril, and P. Chretienne, An algorithm for finding a common structure shared by a family of strings, T-PAMZ 11, 1989, 890-895. 564. P. M. Griffin and C. Alexopoulos, Point pattern matching using centroid bounding, T-SK 19, 1989, 1274-1276. 565. K. Imai, S. Sumino, and H. Imai, Minimax geometric fitting of two corresponding sets of points, CG, 266-275. 566. 0. Marcotte and S. Suri, On geometric matching, CG, 302-314.
G.2. Stereo 567. S. T. Barnard, Stochastic stereo matching over scale, ZJCV 3, 1989, 17-32. 568. G. P. Otto and T. K. W. Chau, “Region-growing” algorithm for matching of terrain images, IVC 7, 1989, 83-94. 569. T. Day and J. P. Muller, Digital elevation model production by stereo-matching SPOT image pairs: a comparison of two algorithms, NC 7, 1989, 95-101. 570. Z. D. Hua and B. Dubuisson, String matching for stereo vision, PRL 9, 1989, 117-126. 571. T. C. Pong, R. M. Haralick, and L. G. Shapiro, Matching topographic structures in stereo vision, PRL 9, 1989, 127-136. 572. F. E. E. Omoruto and J. P. Raina, Concise vector equations for stereopsis, PRL 9, 1989, 367-372. 573. R. March, A regularization model for stereo vision with controlled continuity, PRL 10, 1989, 259-263.
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574. R. Mohan, G. Medioni, and R. Nevatia, Stereo error detection, correction, and evaluation, T-F’Ah4I 11, 1989, 113-120. 575. W. Hoff and N. Ahuja, Surfaces from stereo: integrating feature matching, disparity estimation. and contour detection, T-PAMI 11, 1989, 121-136. 576. Y. Yeshurun and E. L. Schwartz, Cepstral filtering on a columnar image architecture: a fast algorithm for binocular stereo segmentation, T-PAMI 11, 1989, 759-767. 577. Y. C. Shah, R. Chapman, and R. B. Mahani, A new technique to extract range information from stereo images, T-PAMZ 11, 1989, 768-773. 578. N. AIvertos, D. Brzakovic, and R. C. Gonzalez, Camera geometries for image matching in 3-D machine vision, T-PAMZ 11, 1989, 897-915. 579. R. Horaud and T. Skordas, Stereo correspondence through feature grouping and maximal cliques, T-PAMI 11, 1989, 1168-1180. 580. D. Weinshall, Qualitative shape from stereo, IUW, 850-856. 581. S. D. Cochran and G. Medioni, Accurate surface description from binocular stereo, IIJW. 857-869. 582. S. T. Barnard, Stochastic stereo matching on the Connection Machine, IUW, 1021-1031.
583. A. D. Jepson and M. R. M. Jenkin, The fast computation of disparity from phase differences. CVPR, 398-403.
584. T. J. Olson and R. D. Potter, Real-time vergence control, CVPR, 404-409. 585. L. B. Wolff, Accurate measurement of orientation from stereo using line correspondence, CVPR, 410-415. 586. L. Cohen, L. Vinet, P. T. Sander, and A. Gagalowicz, Hierarchical region based stereo matching. CVPR, 416-421. 597. T. Morita, Y. Yasukawa, Y. Inamoto, T. Uchiyama, and S. Kawakami, Measurement in three dimensions by motion stereo and spherical mapping, CVPR, 422-428. 588. A. E. Kayaalp, A. R. Rao, and R. Jain, Scanning electron microscope based stereo analysis. CVPR, 429-434.
589. J. R. Jordan III, A. C. Bovik, and W. S. Geisler, Chromatic stereopsis, IJCAI, 164991654. 590. L. B. Wolff and T. E. Boult, Using line correspondence stereo to measure surface orientation, IJCAI, 1655-1660. 591. G. Xu, H. Kondo, and S. Tsuji, A region-based stereo algorithm, IJCAI, 1661-1666. 592. R. P. Wildes, An analysis of stereo disparity for the recovery of three-dimensional scene geometry, WI3DS, 2-8. 593. S. Das and N. Ahuja, Integrating multiresolution image acquisition and coarse-to-fine surface reconstruction from stereo, WI3DS, 9-15. 594. S. D. Cochran and G. Medioni, Accurate surface description from binocular stereo, WI3DS. 16-23. 595. R. Vaillant and 0. D. Faugeras, Using occluding contours for recovering shape properties of
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600. N. Kehtarnavaz and S. Mohan, A framework for estimation of motion parameters from range images, CVGIP 45, 1989, 88-105. 601. S. P. Liou and R. C. Jain, Motion detection in spatio-temporal space, CVGIP 45, 1989, 227-250. 602. X. Zhuang, A simplification to linear two-view motion algorithms, CVGZP 46, 1989, 175-178. 603. S. Negahdaripour and B. K. P. Horn, A direct method for locating the focus of expansion, CVGIP 46, 1989, 303-326. 604. K. Skifstad and R. Jain, Illumination sequences, CVGIP 46, 1989, 387-399.
independent change detection for real world image
605. A. Mitiche, 0. Faugeras, and J. K. Aggarwal, Counting straight lines, CVGIP 47, 1989, 353-360. 606. P. Anandan, A computational framework and an algorithm, for the measurement of structure from motion, IJCV 2, 1989, 283-310.
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607. J. J. Wu, R. E. Rink, T. M. Caelli, and V. G. Gourishankar, Recovery of the 3-D location and motion of a rigid object through camera image (an extended Kalman filter approach), ZJCV 2, 1989,373-394. 608. F. Bergholm, Motion from flow along contours: a note on robustness and ambiguous cases, ZZCV 2, 1989, 395-415. 609. H. H. Baker and R. C. Bolles, Generalizing epipolar-plane image analysis on the spatiotemporal surface, ZZCV 3, 1989, 33-49. 610. H. H. Baker, Building surfaces of evolution: the weaving wall, ZZCV 3, 1989, 51-71. 611. A. L. Yuille and N. M. Grzywacz, A mathematical analysis of the motion coherence theory, ZJCV 3, 1989, 155-175. 612. D. W. Murray, D. A. Castelow, and B. F. Buxton, From image sequences to recognized moving polyhedral objects, ZJCV 3, 1989, 181-208. 613. L. Matthies, T. Kanade, and R. Szeliski, Kalman filter-based algorithms for estimating depth from image sequences, ZJCV 3, 1989, 209-236. 614. S. Negahdaripour, Critical surface pairs and triplets, ZJCV 3, 1989, 293-312. 615. D. Charnley and R. Blissett, Surface reconstruction from outdoor image sequences, ZVC 7, 1989, 10-16. 616. M. Stephens and C. Harris, 3D wire-frame integration from image sequences, II/C 7, 1989, 24-30. 617. K. J. Hanna and L. Tarassenko, Tracking cataract by the “four-line” method, IVC 7, 1989, 57-62. 618. I. Hadani and E. Barta, The hybrid constraint equation for motion extraction, NC 7, 1989, 217-224. 619. T. J. Broida and R. Chellappa, Performance bounds for estimating three-dimensional motion parameters from a sequence of noisy images, JO&l A6, 1989, 879-889. 620. R. Jasinschi and A. Yuille, Nonrigid motion and Regge calculus, JOSA A6, 1989, 1088-1095. 621. K. Skifstad and R. Jain, Range estimation from intensity gradient analysis, WA 2, 1989,81-102. 622. V. S. S. Hwang, Tracking feature points in time-varying images using an opportunistic selection approach, PR 22, 1989, 247-256. 623. A. Mitiche and G. Habelrih, Interpretation of straight line correspondences using angular relations, PR 22, 1989, 299-308. 624. C. M. Jong and E. Salari, Analysis of image deformation under orthographic projection and flow parameter estimation, PR 22, 1989, 309-315. 625. T. L. Huntsberger and S. N. Jayaramamurthy, Determination of the optic flow field in the presence of occlusion, PZU 8, 1988, 325-333. 626. S. H. Lai and S. Chang, Estimation of 3-D translational motion parameters via Hadamard transform, PRL 8, 1988, 341-345. 627. I. Dinstein, A new technique for visual motion alarm, PRL 8, 1988, 347-351. 628. J. Arnspang, On the use of the horizon of a translating planar curve, PRL 10, 1989, 61-69. 629. J. Arnspang and J. Ma, Image irradiance equations for a zooming camera, PZU 10, 1989, 189-194. 630. C. W. Fu and S. Chang, A motion estimation algorithm under time-varying illumination, PZU 10, 1989, 195-199. 631. D. D. Giusto and G. Vemazza, Optical flow calculation from feature space analysis through an automatic segmentation process, SP 16, 1989, 41-51. 632. G. Tziritas, Recursive and/or iterative estimation of the two-dimensional velocity field and reconstruction of three-dimensional motion, SP 16, 1989, 53-72. 633. T. Reuter, Standards conversion using motion compensation, SP 16, 1989, 73-82. 634. M. Hoetter, Differential estimation of the global motion parameters zoom and pan, SP 16, 1989, 249-265. 635. A. Mecocci, Moving object recognition and classification in external environments, SP 18, 1989, 183-194. 636. W. Y. Choi and R. H. Park, Motion vector coding with conditional transmission, SP 18, 1989, 259-267. 637. T. J. Patterson, D. M. Chabries, and R. W. Christiansen, Detection algorithms for image sequence analysis, T-ASSP 37, 1989, 1454-1458.
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638. H. H. Nagel, On a constraint equation for the estimation of displacement rates in image sequences, T-PAMI 11, 1989, 13-30. 639. M. Subbarao, Interpretation of image flow: a spatio-temporal approach, T-PAM1 11, 1989, 266-278. 640. D. J. Fleet and A. D. Jepson, Hierarchical filters, T-PAMZ 11, 1989, 315-325.
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641. J. Weng, T. S. Huang, and N. Ahuja, Motion and structure from two perspective views: algorithms, error analysis, and error estimation, T-PAMZ 11, 1989, 451-476. 642. G. Adiv, Inherent ambiguities in recovering 3-D motion and structure from a noisy flow field. T-PAMZ 11, 1989,477-480.
643. A. Verri and T. Poggio, Motion field and optical flow: qualitative properties, T-PAMZ 11, 1989. 490-498. 644. J. Aisbett,
Optical flow with an intensity-weighted smoothing, T-PAMZ 11, 1989, 512-522. 645. M. A. Snyder, The precision of 3-D parameters in correspondence-based techniques: the case of uniform translational motion in a rigid environment, T-PAMZ 11, 1989, 523-528. 646. M. Yamamoto, A general aperture problem for direct estimation of 3-D motion parameters. T-PAMZ 11, 1989, 528-536.
647. T. S. Huang and C. H. Lee, Motion and structure from orthographic projections, T-PAMZ 11, 1989, 536-540. 648. A. Mitiche, A comment on “On kineopsis and computation of structure and motion.” T-PAM1 11, 1989, 540-541.
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650. B. G. Schunck, Image flow segmentation and estimation by constraint line clustering, T-PAMZ 11, 1989, 1010-1027. 651. R. C. Nelson and J. (Y.) Aloimonos, Obstacle avoidance using flow field divergence, T-PAM1 11. 1989, 1102-1106. 652 T. S. Huang and 0. D. Fagueras, Some properties of the E matrix in two-view motion estimation, T-PAMZ 11, 1989, 1310-1312. 653. W. M. Wells III, Visual estimation of 3-D line segments from motion--a mobile robot vision system, T-R4 5, 1989, 820-825. 654. J. J. Leou and W. H. Tsai, New sensing strategies for monitoring moving polyhedral objects by machine vision, T-SMC 19, 1989, 872-880. 655. I. D. Horswill and R. A. Brooks, Situated vision in a dynamic world: chasing objects, AAAI. 796-800. 656. P. J. Burt, J. R. Bergen, R. Hingorani, R. Kolczynski, W. A. Lee, A. Leung, J. Lubin, and H.
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703. K. Gould and M. Shah, The trajectory primal sketch: a multi-scale scheme for representing motion characteristics, CVPR, 79-85. 704. J. Wu, R. Brockett, and K. Wohn, A contour-based recovery of image flow: iterative method, CVPR, 124-129. 705. C. S. Fuh and P. Maragos, Region-based optical flow estimation, CVPR, 130-135. 706. R. V. Raja Kumar, A. Tirumalai, and R. C. Jain, A non-linear optimization algorithm for the estimation of structure and motion parameters, CVPR, 136-143. 707. J. Weng, N. Ahuja, and T. S. Huang, Optimal motion and structure estimation, CVPR, 144-152. 708. J. F. Bronskill, J. S. A. Hepburn, and W. K. Au, A knowledge-based approach to the detection, tracking and classification of target formations in infrared image sequences, CVPR, 153-158. 709. R. Dutta, R. Manmatha, L. R. Williams, and E. M. Riseman, A data set for quantitative motion analysis, CVPR, 159-164. 710. F. Jiang and T. E. Weymouth, Depth from dynamic stereo images, CVPR, 250-255. 711. S. Chaudhuri and S. Chatterjee, Estimation of motion parameters for a deformable object from range data, CVPR, 291-295. 712. D. J. Fleet and A. D. Jepson, Computation of normal velocity from local phase information, CVPR, 379-386. 713. M. J. Stephens, R. J. Blissett, D. Charnley, E. P. Sparks, and J. M. Pike, Outdoor vehicle navigation using passive 3D vision, CVPR, 556-562. 714. W. Burger and B. Bhanu, On computing a “fuzzy” focus of expansion for autonomous navigation, CVPR, 563-568. 715. Y. F. Wang and A. Pandey, Interpretation of 3D structure and motion using structured lighting, WI3DS, 84-90. 716. M. Xie and P. Rives, Towards dynamic vision, WI3DS, 91-99. 717. C. Brown, Kinematic and 3D motion prediction for gaze control, WI3DS, 145-151. 718. The Visual Processing of Motion (C.N.R.S. Jacques Monod Conference), Roscoff, France, June 19-23, 1989. 719. C. Chubb and G. Sperling, Second-order motion perception: space/time separable mechanisms, WVM, 126-138. 720. R. S. Jasinschi, Towards a theory of apparent visual motion, WVM, 139-147. 721. N. M. Grzywacz, J. A. Smith, and A. L. Yuille, A common theoretical framework for visual motion’s spatial and temporal coherence, WVM, 148-155. 722. A. M. Waxman, J. Wu, and M. Seibert, Computing visual motion in the short and the long: from receptive fields to neural networks, WVM, 156-164. 723. H. H. Biilthoff, J. J. Little, and T. Poggio, A parallel motion algorithm consistent with psychophysics and physiology, WVM, 165-172. 724. J. M. Loomis and D. W. Eby, Relative motion parallax and the perception of structure from motion, WVM, 204-211. 725. N. H. Goddard, The interpretation of visual motion: recognizing moving light displays, WVM, 212-220. 726. (L. Liu), (N. Zhao), and (Z. Bian), Can early stage vision detect topology, IJCAI, 1591-1595.
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ROSENFELD
733. A. Y. Wu, S. K. Bhaskar, and A. Rosenfeld, Parallel processing of region boundaries, PR 22, 1989, 165-172. 734. N. Kiryati and D. Maydan, Calculating geometric properties from Fourier representation, PR 22, 1989,469-475. 735. R. E. Webber and M. B. Dillencourt, Compressing quadtrees via common subtree merging, PZU 9, 1989, 193-200. 736. L. P. Cordella and G. Sanniti di Baja, Geometric properties of the union of maximal neighborhoods, T-PAMI 11, 1989,214-217. 737. J. Goutsias and D.Schonfeld, Image coding via morphological transformations: a general theory, CVPR, 178-183. 738. S. T. Huang and M. S. Tsai, A linear systolic algorithm for the connected component problem, BIT 29, 1989, 217-226. 739. T. Y. Kong, A digital fundamental group, C& G 13, 1989, 159-166. 740. W. P. Horn and D. L. Taylor, A theorem to determine the spatial containment of a point in a planar polyhedron, CVGZP 45, 1989, 106-116. 741. M. Manohar and H. K. Ramapriyan, Connected component labeling of binary images on a mesh connected massively parallel processor, CVGZP 45, 1989, 133-149. 742. V. A. Kovalevski, Finite topology as applied to image analysis, CVGZP 46, 1989, 141-161. 743. Z. C. Shih, R. C. T. Lee, and S. N. Yang, A systolic algorithm for extracting regions from a planar graph, CVGZP 47, 1989, 227-242. 744. T. Y. Kong and A. Rosenfeld, Digital topology: introduction and survey, CVGZP 48, 1989, 357-393. 745. G. Cybenko, T. G. Allen, and J. E. Polito, Practical parallel union-find algorithms for transitive closure and clustering, Zntl. J. Parallel Programming 17, 1988, 403-423. 746. R. Cypher, Hypercube and shuffle-exchange algorithms for image component labeling, .Z. Algoritfms 10, 1989, 140-150. 747. M. H. Chen and P. F. Yan, A fast algorithm to calculate the Euler number for binary images, PRL 8, 1988, 295-297. 748. R. A. Melter and A. Rosenfeld, New views of linearity and connectedness in digital geometry, PZU. 10, 1989, 9-16. 749. T. Lengauer and E. Wanke, Efficient solution of connectivity problems on hierarchically defined graphs, SLAM JC 17, 1988, 1063-1080. 750. R. Cypher, J. L. C. Sanz, and L. Snyder, An EREW PRAM algorithm for image component labeling, T-PAh4Z 11, 1989, 258-262. 751. E. Brisson, Representing geometric structures in d dimensions: topology and order, CG, 218-227. 752. V. J. Milenkovic, Verifiable implementations of geometric algorithms using finite precision arithmetic, AZ 37, 1988, 377-401. 753. A. Fleming, Geometric relationships between toleranced features, AZ 37, 1988, 403-412. 754. C. M. Hollinann, The problems of accuracy and robustness in geometric computation, Computer 22 (31, 1989, 31-41. 755. K. Sugihara, On finite-precision representations of geometric objects, ZCSS 39, 1989, 236-247. 756. D. I. Havelock, Geometric precision in noise-free digital images, T-PAMZ 11, 1989, 1065-10755. 757. V. J. Milenkovic, Robust geometric computations for vision and robotics, IUW, 764-773.
H.2. Curves, etc. 758. I. Wilf and Y. Manor, Tracking parameterized algebraic curves on raster displays, C&G l3, 1989,355-359. 759. X. Wu and J. G. Rokne, Double-step generation of ellipses, CGA 9(3), 1989, 56-69. 760. I. Galton, An efficient three-point arc algorithm, CGA 9(6), 1989, 44-49. 761. W. G. Kropatsch and H. Tockner, Detecting the straightness of digital curves in O(N) steps, CVGZP 45, 1989, l-21. 762. D. J. Walton, A note on graphics editing of curved line drawings, CVGZP 45, 1989, 61-67. 763. J. Dassow, Graph-theoretical properties and chain code picture languages, EIK 25, 1989, 423-433. 764. D. G. Lowe, Organization of smooth image curves at multiple scales, ZJCV 3, 1989, 119-130. 765. R. I. Hartley, Drawing polygons given angle sequences, ZPL 31, 1989,31-33.
IMAGE ANALYSIS AND COMPUTER
VISION:
1989
217
766. H. Ogawa, Corner detection on digital curves based on local symmetry of the shape, PR 22, 1989. 351-357. 767. A. E. Middleditch, T. W. Stacey, and S. B. Tor, Intersection algorithms for lines and circles, TOG 8, 1989, 25-40. 768. G. Farin, Curvature continuity and offsets for piecewise tonics, TOG 8, 1989, 89-99. 769. M. C. Stone and T. D. DeRose, A geometric characterization of parametric cubic curves, TOG 8, 1989, 147-163. 770. R. Sriraman, J. Koplowitz, and S. Mohan, Tree searched chain coding for subpixel reconstruction of planar curves, T-PAM1 11, 1989, 95-104. 771. X. Wu and J. Rokne, On properties of discretized convex curves, T-PAM1 11, 1989, 217-223. 772. C. H. Teh and R. T. Chin, On the detection of dominant points on digital curves, T-PAMI 11, 1989, 859-872. 773. B. Kartikeyan and A. Sarkar, Shape description by time series, T-PAMI 11, 1989, 977-984. 774. S. Biswas and S. K. Pal, Approximate coding of digital contours, T-SMC’18, 1988, 1056-1066. 775. S. Pham, Parallel, overlapped, and intersected digital straight lines, VC 4, 1988, 247-258. 776. E. Kaltofen, Computing the irreducible real factors and components of an algebraic curve, CG. 79-87. 777. S. S. Abhyankar, S. Chandrasekar, and V. Chandru, Degree complexity bounds on the intersection of algebraic curves, CG, 88-93. 778. A. Arokiasamy, Homogeneous coordinates and the principle of duality in two dimensional clipping, C& G 13, 1989, 99-100. 779. A. Margalit and G. D. Knott, An algorithm for computing the union, intersection or difference of two polygons, C& G 13, 1989, 167-183. 780. S. Forchhammer, Digital plane and grid point segments, CVGIP 47, 1989, 373-384.
H.3.
Distance, Skeletons
781. R. W. Hall, Fast parallel thinning algorithms: parallel speed and connectivity preservation, Comm. A C M 32, 1989, 124-131. 782. Z. Guo and R. W. Hall, Parallel thinning with two-subiteration algorithms, Comm. A C M 32, 1989, 359-373. 783. A. L. D. Beckers and A. W. M. Smeulders, A comment on “A note on distance transformations in digital images,” CVGIP 47, 1989, 89-91. 784. H. Beffert and R. Shinghal, Skeletonizing binary patterns on the homogeneous multiprocessor, IJPRAI 3, 1989, 207-216. 785. J. E. Bobrow, A direct minimization approach for obtaining the distance between convex polyhedra, IJRR 8 (3), 1989, 65-76. 786. R. Shonkwiler, An image algorithm for computing the Hausdortf distance efficiently in linear time, IPL 30, 1989, 87-89. 787. J. C. Culberson and P. Rudnicki, A fast algorithm for constructing trees from distance matrices, IPL 30, 1989, 215-220. 788. P. P. Das and B. N. Chatterji, Estimation of errors between Euclidean and m-neighbor distance. IS 48, 1989, l-26. 789. G. L. Scott, S. C. Turner, and A. Zisserman, Using a mixed wave-diffusion process to elicit the symmetry set, IVC 7, 1989, 63-70. 790. C. Holt and A. Stewart, A parallel thinning algorithm with fine grain subtasking, PC 10, 1989. 329-334. 791. Y. S. Chen and W. H. Hsu, A systematic approach for designing 2-subcycle and pseudo-subcycle parallel thinning algorithms, PR 22, 1989, 267-282. 792. N. G. Bourbakis, A parallel-symmetric thinning algorithm, PR 22, 1989, 387-396. 793. G. Borgefors, Distance transformations on hexagonal grids, PRL 9, 1989, 97-105. 794. P. P. Das, An algorithm for computing the number of the minimal paths in digital images, PRL 9, 1989, 107-116. 795. S. K. Pal, Fuzzy skeletonization of an image, PRL 10, 1989, 17-23. 796. P. P. Das, More on path generated digital metrics, PRL 10, 1989, 25-31. 797. P. P. Das, Metric&y preserving transforms, PRL 10, 1989, 73-76. 798. J. H. Sossa, An improved parallel algorithm for thinning digital patterns, PRL 10, 1989, 77-80.
218
AZRIEL
ROSENFELD
799. J. Mukherjee and B. N. Chatterji, Thinning of 3-D images using the Safe Point Thinning Algorithm @PTA), PRL. 10, 1989, 167-173. 800. F. Meyer, Skeletons and perceptual graphs, SP 16, 1989,335-363. 801. P. S. P. Wang and Y. Y. Zhang, A fast and flexible thinning algorithm, T-COMP 38, 1989, 741-745. 802. C. Arcelli and G. Sanniti di Baja, A one-pass two-operation process to detect the skeletal pixels on the 4-distance transform, T-PAMI 11, 1989, 411-414. 803. B. J. H. Verwer, P. W. Verbeek, and S. T. Dekker, An efficient uniform cost algorithm applied to distance transforms, T-PAMZ 11, 1989, 424-429. 804. E. Wolfson and E. L. Schwartz, Computing minimal distances on polyhedral surfaces, T-PNZ 11, 1989, 1001-1005. 805. Y. Xia, Skeletonization via the realization of the fire front’s propagation and extinction in digital binary shapes, T-PAMI 11, 1989, 1076-1086. 806. Y. S. Chen and W. H. Hsu, A 1-subcycle parallel thinning algorithm for producing perfect b-curves and obtaining isotropic skeleton of an Lshape pattern, CVPR, 208-215.
H.4. Properties, Recognition 807. W. C. Lin, C. C. Liang, and C. T. Chen, A computational model for process-grammar, AZ 38, 1989, 207-224. 808. S. S. Skiena, Problems in geometric probing, Algorithmicn 4, 1989, 599-605. 809. S. M. Thomas and Y. T. Chan, A simple approach for the estimation of circular arc center and its radius, CVGIP 45, 1989, 362-370. 810. J. A. Gualtieri, S. Baugher, and M. Werman, The visual potential: one convex polygon, CVGIP 46, 1989, 96-130. 811. G. Marola, Using symmetry for detecting and locating objects in a picture, CVGZP 46, 1989, 179-195. 812. D. Kijlzow, A. Kuba, and A. Volcic, An algorithm for reconstructing convex bodies from their projections, DCG 4, 1989, 205-237. 813. Y. T. Tsay and W. H. Tsai, Model-guided attributed string matching by split-and-merge for shape recognition, IJPRAI 3, 1989, 159-179. 814. A. Bryant and J. Bryant, Recognizing shapes in planar binary images, PR 22, 1989, 155-164. 815. C. L. Chen, Computing the convex hull of a simple polygon, PR 22, 1989, 561-565. 816. Z. Hussein, A fast approximation to a convex hull, PRL 8, 1988, 289-294. 817. (M. Zhu), S. Hasani, S. Bhattarai, and H. Singh, Pattern recognition with moment invariants on a machine vision system, PRL 9, 1989, 175-180. 818. K. S. Ray and D. Dutta Majumder, Application of differential geometry to recognize and locate partially occluded objects, PRL 9, 1989, 351-360. 819. H. I. Stern, Polygonal entropy: a convexity measure, PRL 10, 1989, 229-235. 820. R. Takiyama and N. Ono, A least square error estimation of the center and radii of concentric arcs, PRL 10, 1989, 237-242. 821. P. Seitz, The robust recognition of object primitives using local axes of symmetry, SP 18, 1989, 89-108. 822. G. Marola, On the detection of the axes of symmetry of symmetric and almost symmetric planar images, T-PAMI 11, 1989, 104-108. 823. C. Ronse, A bibliography on digital and computational convexity (1961-19881, T-PAMZ 11, 1989, 181-190. 824. J. Koplowitz and A. M. Bruckstein, Design of perimeter estimators for digitized planar shapes, T-PAMI 11, 1989,611-622. 825. C. H. Lo and H. S. Don, 3-D moment forms: their construction and application to object identification and positioning, T-PAhfZ 11, 1989, 1053-1064. 826. S. Y. Shin and T. C. Woo, An optimal algorithm for finding all visible edges in a simple polygon, T-R/l 5, 1989, 202-207.
827. G. C. Burdea and H. J. Wolfson, Solving jigsaw puzzles by a robot, TX4 5, 1989, 752-764. 828. A. Taza and C. Y. Suen, Discrimination of planar shapes using shape matrices, T-SMC 19, 1989, 1281-1289. 829. K. Rao and R. Nevatia, Descriptions of complex objects from incomplete and imperfect data, Iuw, 399-414.
IMAGE ANALYSIS AND COMPUTER
VISION:
1989
219
830. A. Khotanzad and J. H. Lu, Object recognition using a neural network and invariant Zernike features, CVPR, 200-205. 831. G. Taubin, R. M. Bolle, and D. B. Cooper, Representing and comparing shapes using shape polynomials, CVPR, 510-516. 832. P. J. Hayes and M. Leyton, Processes at discontinuities, IJCAI, 1267-1272. 833. F. J. Vasko, F. E. Wolf, and K. L. Stott, A practical solution to a fuzzy two-dimensional cutting stock problem, FSS 29, 1989,259-275. 834. X. Markenscoff and C. H. Papadimitriou, Optimum grip of a polygon, IJRR 8 (21, 1989, 17-29. 835. J. C. Trinkle and R. P. Paul, The initial grasp liftability chart, T-RA 5, 1989, 47-52.
H.5.
Motion and Path Planning;
Mapping
836. K. Sutner and W. Maass, Motion planning among time dependent obstacles, Acta Infomatica 26, 1988, 93-122. 837. J. T. Schwartz and M. Sharir, A survey of motion planning and related geometric algorithms, AZ 37, 1988, 157-169. 838. J. S. B. Mitchell, An algorithmic approach to some problems in terrain navigation, AI 37, 1988, 171-201. 839. J. Canny, Constructing roadmaps of semi-algebraic sets I: Completeness, AI 37, 1988, 203-222. 840. B. R. Donald, A geometric approach to error detection and recovery for robot motion planning with uncertainty, AI 37, 1988, 233-271. 841. C. L. Bajaj and M. S. Kim, Generation of configuration space obstacles: the case of moving algebraic curves, Algorithmica 4, 1989, 157-172. 842. M. Shairir, Algorithmic motion planning in robotics, Computer 22 (3), 1989, 9-20. 843. T. Lozano-Perez, J. L. Jones, E. Mazer, and P. A. O’Donnell, Task-level planning of pick-andplace robot motions, Computer 22(3), 1989, 21-29. 844. P. J. de Rezende, D. T. Lee, and Y. F. Wu, Rectilinear shortest paths in the presence of rectangular barriers, DCG 4, 1989, 41-53. 845. L. J. Guibas, M. Sharir, and S. Sifrony, On the general motion-planning problem with two degrees of freedom, DCG 4, 1989,491-521. 846. C. E. Buckley, A foundation for the “flexible-trajectory” approach to numeric path planning. IJRR 8 (31, 1989, 44-64. 847. B. Steer, Trajectory planning for a mobile robot, IJRR 8 (5), 1989, 3-14. 848. S. J. Buckley, Planning compliant motion strategies, IJRR 8 (5), 1989, 28-44. 849. C. W. Warren, J. C. Danos, and B. W. Mooring, An approach to manipulator path planning, IJRR 8 (5), 1989, 87-95. 850. J. S. Provan, Shortest enclosing walks and cycles in embedded graphs, IPL 30, 1989, 119-125 851. E. B. Feinberg, Characterizing the shortest path of an object among obstacles, IPL 31, 1989, 257-264. 852. M. Sharir, A note on the Papadimitriou-Silverberg algorithm for planning optimal piecewise-hnear motion of a ladder, IPL 32, 1989, 187-190. 853. B. K. Bhattacharya and J. Zorbas, Solving the two-dimensional findpath problem using a line-triangle representation of the robot, J. Algorithms 9, 1988, 449-469. 854. E. B. Feinberg and C. H. Papadimitriou, Finding feasible paths for a two-point body, J. Algorithms 10, 1989, 109-119. 855. F. Dehne, A. L. Hassenklover, and J. R. Sack, Computing the configuration space for a robot on a mesh-of-processors, PC 12, 1989, 221-231. 856. K. Fujimura and H. Samet, A hierarchical strategy for path planning among moving obstacles. T-RA 5, 1989, 61-69. 857. 0. Takahashi and R. J. Schilling, Motion planning in a plane using generalized Voronoi diagrams, T-RA 5, 1989, 143-150. 858. E. Cheung and V. J. Lumelsky, Proximity sensing in robot manipulator motion planning: system and implementation issues, T-RA 5, 1989, 740-751. 859. J. Borenstein and Y. Koren, Real-time obstacle avoidance for fast mobile robots, T-SA4C 19, 1989, 1179-1187. 860. Y. Hwang and N. Ahuja, Path planning using a potential field representation, CVPR, 569-575. 861. D. Halperin and M. H. Gvermars, Efficient motion planning for an L-shaped object, CG, 156-166.
220
AZRIEL
ROSENFELD
862. L. P. Chew and K. Kedem, Placing the largest similar copy of a convex polygon among polygonal obstacles, CG, 167-174. 863: J. Friedman, J. Hershberger, and J. Snoeyink, Compliant motion in a simple polygon, CG, 175-186. 864. A. J. Briggs, An efficient algorithm for one-step planar compliant motion planning with uncertainty, CG, 187-196. 865. E. M. Arkin, R. Connelly, and J. S. B. Mitchell, On monotone paths among obstacles, with applications to planning assemblies, CG, 334-343. 866. L. Tychonievich, D. Zaret, J. Mantegna, R. Evans, E. Muehle, and S. Martin, A maneuveringboard approach to path planning with moving obstacles, IJCAI, 1017-1021. 867. B. Zhang, L. Zhang, and T. Zhang, Motion planning of multi-joint robotic arm with topological dimension reduction method, IJCAI, 1029-1034. 868. B. Faltings, E. Baechler, and J. Primus, Reasoning about kinematic topology, IJCAI, 1331-1336. 869. A. Hemmerling, Labyrinth Problems-Labyrinth-Searching Abilities of Automata, Teubner, Leipzig, 1989. 870. A. Elfes, Using occupancy grids for mobile robot perception and navigation, Computer 22 (61, 1989,46-57. 871. Y. Roth-Tabak and R. Jain, Building an environment model using depth information, Computer 22 (6), 1989, 85-90. 872. R. C. Arkin, Motor schema-based mobile robot navigation, IJRR 8 (41, 1989, 92-112. 873. N. Ayache and 0. D. Faugeras, Maintaining representations of the environment of a mobile robot, T-RA 5, 1989, 804-819. 874. B. J. Kuipers and Y. T. Byun, A robust, qualitative method for robot spatial learning, AAAI, 774-779. 875. E. Davis, Inferring ignorance from the locality of visual perception, AAAI, 786-790 876. K. Basye, T. Dean, and J. S. Vitter, Coping with uncertainty in map learning, IJCAI, 665-668. 877. M. Asada and Y. Shirai, Building a world model for a mobile robot using dynamic semantic constraints, IJCAI, 1629-1634.
I. Color and Texture I.1. Illumination
and Color
878. R. Hall, Illumination and Color in Computer Generated Imagery, Springer, Berlin, 1988. 879. B. Funt and J. Ho, Color from black and white, ZJCV 3, 1989, 109-117. 880. W. A. Wright, A Markov random field approach to data fusion and colour segmentation, NC 7, 1989, 144-150. 881. L. B. Wolff, Material classification and separation of reflection components using polarization/ radiometric information, IUW, 232-244. 882. M. J. Daily, Color image segmentation using Markov random fields, IUW, 552-562, 1149-1151. 883. G. Healey, A parallel color algorithm for segmenting images of 3-D scenes, IUW, 1038-1042. 884. M. J. Daily, Color image segmentation using Markov random fields, CVPR, 304-312. 885. L. B. Wolff, Using polarization to separate reflection components, CVPR, 363-369. 886. L. B. Wolff and T. E. Boult, Polarization/radiometric based material classification, CVPR, 387-395. 887. D. Forsyth and A. Zisserman, Mutual illumination, CVPR, 466-473. 888. B. J. Lindbloom, Accurate color reproduction for computer graphics applications, SIGGRAPH, 117-126.
1.2. Texture: ModeIs, Synthesis H. 0. Peitgen and D. Saupe, The Science of Fractal Images, Springer, Berlin, 1988. M. Barnsley, FractaLFEverywhere, Academic Press, Boston, 1988. J. Shallit and J. Stohi, Two methods for generating fractals, C& G 13, 1989, 185-191. N. Yokoya, K. Yamamoto, and N. Funakubo, Fractal-based analysis of 3D natural surface shapes and their application to terrain modeling, CVGIP 46, 1989, 284-302. 893. P. Boulanger, A. Gagalowicz, and M. Rioux, Integration of synthetic surface relief in range images, CVGZP 47, 1989, 361-372.
889. 890. 891. 892.
IMAGE ANALYSIS AND COMPUTER
VISION
1989
221
894. S. L. Stepoway and M. Christiansen, Parallel rendering of fractal surfaces, Intl J. Parallel Pmgramming 17, 1988, 43-58. 895. H. Derin and P. A. Kelly, Discrete-index Markov-type random processes, P-IEEE 77, 1989. 1485-1510. 896. P. Meer and S. Connelly, A fast parallel method for synthesis of random patterns, PR 22, 1989, 189-204. 897. S. K. Bhaskar, A. Rosenfeld, and A. Wu, Models for neighbor dependency in planar point pattens, PR 22, 1989, 533-559. 898. A. Margalit, A parallel algorithm to generate a Markov random field image on a SIMD hypercube machine, PRL 9, 1989, 263-278. 899. D. Jeulin, Morphological modeling of images by sequential random functions, SP 16, 1989. 403-431. 900. D. S. Jeong and P. M. Lapsa, Unified approach for early-phase image understanding using a general decision criterion, T-PAMZ 11, 1989, 357-371. 901. M. Boudaoud and L. F. Chaparro, Nonstationary composite modeling of images, T-SMC 19, 1989, 112-117. 902. C. A. Pickover, The use of image processing techniques in rendering maps with deterministic chaos, VC 4, 1988, 271-276. 903. C. C. Chen and R. C. Dubes, Experiments in fitting discrete Markov random fields to textures. CVPR, 298-303. 904. X. G. Viennot, G. Eyrolles, N. Janey, and D. Arques, Combinatorial analysis of ramified patterns and computer imagery of trees, SIGGRAPH, 31-40. 905. F. K. Musgrave, C. E. Kolb, and R. S. Mice, The synthesis and rendering of fractal terrains. SIGGRAPH, 41-50. 906. R. Szeliski and D. Terzopoulos, From splines to fractals, SIGGRAPH, 51-60. 907. N. Greene, Voxel space automata: modeling with stochastic growth processes in voxel space. SIGGRAPH, 175-184. 908. K. Perlin and E. M. Hoffert, Hypertexture, SIGGRAPH, 253-262. 909. J. P. Lewis, Algorithms for solid noise synthesis, SIGGRAPH, 263-270. 910. J. T. Kajiya and T. L. Kay, Rendering fur with three dimensional textures, SIGGRAPH, 271-280.
1.3. Texture: Desctiption 911. I. Fogel and D. Sagi, Gabor filters as texture discriminator, BC 61, 1989, 103-113. 912. R. Vistnes, Texture models and image measures for texture discrimination, IJCV 3, 1989, 313-336. 913. J. Garding, Properties of fractal intensity surfaces, PRL 8, 1988, 319-324. 914. P. Cohen, C. T. LeDinh, and V. Lacasse, Classification of natural textures by means of two-dimensional orthogonal masks, T-ASP 37, 1989, 125-128. 915. Z. Liu and Y. Attikiouzel, Two-dimensional linear prediction model-based decorrelation method, T-PAMI 11, 1989, 661-665.
916. M. Amadasun and R. King, Textural features corresponding to textural properties, T-SMC 19, 1989, 1264-1274. 917. L. G. C. Hamey and T. Kanade, Computer analysis of regular repetitive textures, IUW, 1076-1088. 918. A. R. Rao and B. G. Schunck, Computing oriented texture fields, CVPR, 61-68.
1.4. Texture: Segmentation 919. K. Iwama, Merging regions across feature maps in texture segmentation, BC 61, 1989, 295-302. 920. J. M. Keller, S. Chen, and R. M. Crownover, Texture description and segmentation through fractal geometry, CVGZP 45, 1989, 150-166. 921. J. Y. Hsiao and A. A. Sawchuk, Unsupervised textured image segmentation using feature smoothing and probabilistic relaxation techniques, CVGZP 48, 1989, 1-21. 922. C. A. Sher and A. Rosenfeld, Detecting and extracting compact textured regions using pyramids, ZVC 7, 1989, 129-134. 923. R. L. Kashyap and K. B. Eom, Texture boundary detection based on the long correlation model, T-PAM 11, 1989, 58-67.
222
AZRIEL
ROSENFELD
924. A. Khotanzad, Unsupervised segmentation of textured images by edge detection in multidimensional features, T-PAMI 11, 1989, 414-421. 925. M. C. K. Yang and C. C. Yang, Image enhancement for segmentation by self-induced autoregressive filtering, T-PAMZ 11, 1989, 655-661. 926. M. Unser and M. ,Eden, Multiresolution feature extraction and selection for texture segmentation, T-PAMZ 11, 1989, 717-728. 927. J. Y. Hsiao and A. A. Sawchuk, Supervised textured image segmentation using feature smoothing and probabilistic relaxation techniques, T-PAMZ 11, 1989, 1279-1292. 928. A. Perry and D. G. Lowe, Segmentation of textured images, CVPR, 319-325. 929. J. Malik and P. Perona, A computational model of texture segmentation, CVPR, 326-332.
J. Three-Dimensional J.1. 30 Acquisition,
Scene Ana&s
etc.
930. P. Besl, Surfaces in Range Image Understanding, Springer, Berlin, 1988. 931. A. Jain and R. Jain, Range Image Understanding, Springer, Berlin, 1989.
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963. B. Mishra and N. Silver, Some discussion of static gripping and its stability, T-SMC 19, 1989, 783-796. 964. M. Mehdian and H. Rahnejat, A sensory gripper using tactile sensors for object recognition, orientation control, and stable manipulation, T-SMC 19, 1989, 1250-1261. 965. S. A. Stansfield, Reasoning about grasping, AAAI, 768-773.
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973. S. Kamata, S. Ishikawa, and K. Kato, Reconstructing an edge on a polyhedron using an optimization method, CVGIP 47, 1989, 92-104. 974. W. Whiteley, A matroid on hypergraphs, with applications to scene analysis and geometry, DCG 4, 1989,75-95. 975. T. Shakunaga and H. Kaneko, Perspective angle transform: principle of shape from angles, I&X’ 3, 1989 239-254. 976. K. Kanatani, Reconstruction of consistent shape from inconsistent data: optimization of 2fD sketches, IJCV 3, 1989, 261-292. 977. A. Zisserman, P. Giblin, and A. Blake, The information available to a moving observer from
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J.5. Recognition 1129. A. K. Jain, ed., Real-Time Object Measurement and Classijication, Springer, Berlin, 1988. 1130. R. B. Fisher, From Surfaces to Objects-Computer V7ion and Three-Dimensional Scene Analysis, Wiley, Chichester, UK, 1989. 1131. J. E. W. Mayhew and J. P. Frisby, 3D Model Recognition from Stereoscopic Cues, MIT Press, Cambridge, MA, 1989. 1132. S. B. Pollard, T. P. Pridmore, J. Porrill, J. E. W. Mayhew, and J. P. Frisby, Geometrical modeling from multiple stereo views, ZJRR 8 (41, 1989, 3-32. 1133. A. D. Worrall, K. D. Baker, and G. D. Sullivan, Model based perspective inversion, 17/C 7, 1989, 17-23. 1134. D. Holder and H. Buxton, Polyhedral object recognition with sparse data in SIMD processing mode, NC 7, 1989,71-78. 1135. M. C. Yang and W. H. Tsai, Recognition of single 3D curved objects using 2D cross-sectional slice shapes, NC 7, 1989, 210-216. 1136. B. Bhanu and L. A. Nuttall, Recognition of 3-D objects in range images using a Butterfly multiprocessor, PR 22, 1989, 49-64. 1137. K. C. Hung, R. N. Chiou, C. N. Shyi, J. Y. Lee, and C. H. Chen, Polyhedron reconstruction using three-view analysis, PR 22, 1989, 231-246. 1138. I. Wilf and Y. Manor, Multiple-view model-based inspection of quadric objects, PZU 10, 1989, 33-38.
1139. A. K C. Wong, S. W. Lu, and M. Riouz, Recognition and shape synthesis of 3-D objects based on attributed hypergraphs, T-PAMZ 11, 1989, 279-290. 1140. C. H. Chien and J. K. Aggarwal, Model construction and shape recognition from occluding contours, T-PAMZ 11, 1989,372-389. 1141. A. P. Reeves and R. W. Taylor, Identification of three-dimensional objects using range information, T-PAMZ 11, 1989, 403-410. 1142. H.,Wechsler and G. L. Zimmerman, Distributed associative memory (DAM) for bin-picking, T-PAMZ 11, 1989, 814-822.
1143. T. J. Fan, C. Medioni, and R. Nevatia, Recognizing 3-D objects using surface descriptions, T-PAMZ 11, 1989, 1140-1157. 1144. R. Krishnapuram and D. Casasent, Determination of three-dimensional object location and orientation from range images, T-PAMZ 11, 1989, 1158-1167. 1145. C. Hansen and T. C. Henderson, CAGD-based computer vision, T-PAMZ 11, 1989, 1187-1193. 1146. D. B. Goldgof, T. S. Huang, and H. Lee, A curvature-based approach to terrain recognition, T-PAMZ 11, 1989, 1213-1217.
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1147. C. Gurwicz and M. L. Overton, A globally convergent algorithm for minimizing over the rotation group of quadratic forms, T-PAM 11, 1989, 1228-1232. 1148. M. Dhome, M. Richetin, J. T. Lapreste, and G. Rives, Determination of the attitude of 3-D objects from a single perspective view, T-PAMZ 11, 1989, 1265-1278. 1149. J. Jurczyk and K. A. Loparo, Mathematical transforms and correlation techniques for object recognition using tactile data, T-M 5, 1989, 359-362. 1150. J. W. Roach, P. K. Paripati, and M. Wade, Model-based object recognition using a large-field passive tactile sensor, T-WC 19, 1989, 846-853. 1151. R. W. Taylor and A. P. Reeves, Classification quality assessment for a generalized model-based object identification system, T-SK 19, 1989, 861-866. 1152. T. 0. Binford, Spatial understanding: the SUCCESSOR System, IUW, 12-20. 1153. J. Ponce and D. J. Kriegman, On recognizing and positioning curved 3D objects from image contours, IUW, 461-470. 1154. T. M. Breuel, Adaptive model base indexing, IUW, 805-814. 1155. D. Cyrluk and D. Kapur, Reasoning about nonlinear inequality constraints: a multi-level approach, IUW, 904-915. 1156. A. J. Heller and J. R. Stenstrom, Verification of recognition and alignment hypotheses by means of edge verification statistics, IUW, 957-966. 1157. D. W. Thompson, Edge based transform refinement, IUW, 1070-1075. 1158. Y. Yacoob and Y. I. Gold, 3D object recognition via simulated particles diffusion, CVPR, 442-449.
1159. K. Ikeuchi and K. S. Hong, Determining linear shape change: toward automatic generation of object recognition programs, CVPR, 450-457. 1160. S. A. Hutchinson, R. I. Cromwell, and A. C. Kak, Applying uncertainty reasoning to model based object recognition, CVPR, 541-548. 1161. R. M. Bolle, A. Califano, R. Kjeldsen, and R. W. Taylor, Visual recognition using concurrent and layered parameter networks, CVPR, 625-631. 1162. R. Kjeldsen, R. M. Bolle, A. Califano, and R. W. Taylor, A homogeneous framework for visual recognition, IJCAI, 1578-1584. 1163. J. Ponce and D. J. Kriegman, On recognizing and positioning curved 3D objects from image contours, WI3DS, 61-67. 1164. R. Bergevin and M. D. Levine, Generic object recognition: building coarse descriptions from line drawings, WI3DS, 68-74. 1165. S. Lee and H. S. Hahn, Object recognition and localization using optical proximity sensor system: polyhedral case, WI3DS, 75-81. 1166. P. G. Mulgaonkar, C. K. Cowan, and J. DeCurtins, Scene description using range data, WI3DS. 138-144.
J.6. Miscellaneous 1167. E. L. Walker and M. Herman, Geometric reasoning for constructing 3D scene descriptions from images, AZ 37, 1988, 275-290. 1168. M. Barry, D. Cyrluk, D. Kapur, J. Mundy, and V. D. Nguyen, A multi-level geometric reasoning system for vision, AZ 37, 1988, 291-332. 1169. J. Raczkowsky and K. H. Mittenbuehler, Simulation of cameras in robot applications, CGA 9 (1). 1989, 16-25. 1170. K. Ikeuchi and T. Kanade, Modeling sensors: toward automatic generation of object recognition program, CVGZP 48, 1989, 50-79. 1171. P. K. Allen, Integrating vision and touch for object recognition tasks, ZJRR 7 (61, 1988, 15-33. 1172. S. Shekhar, 0. Khatib, and M. Shimojo, Object localization with multiple sensors, ZJZtR 7 (6). 1988, 34-44. 1173. N. Ayache and 0. D. Faugeras, Building, registrating, and fusing noisy visual maps, ZJRR 7 (6). 1988, 45-65. 1174. J. Porrill, Optimal combination and constraints for geometrical sensor data, ZJRR 7 (61, 1988. 66-77.
1175. J. M. Richardson and K. A. Marsh, Fusion of multisensor data, ZJRR 7 (6), 1988, 78-96. 1176. H. F. Durrant-Whyte, Sensor models and multisensor integration, ZJZZR7 (61, 1988, 97-113.
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1177. T. Henderson, E. Weitz, C. Hansen, and A. Mitiche, Multisensor knowledge systems: interpreting 3D structure, ZJRR 7 (61, 1988, 114-137. 1178. S. A. Stansfield, A robotic perceptual system utilizing passive vision and active touch, ZJZtR 7 (6), 1988, 138-161. 1179. Y. Yeshurun and E. L. Schwartz, Shape description with a space-variant sensor: algorithms for scan-path, fusion, and convergence over multiple scans, T-PAMI 11, 1989, 1217-1222. 1180. S. A Hutchinson and A. C. Kak, Planning sensing strategies in a robot work cell with multi-sensor capabilities, T-M 5, 1989, 765-783. 1181. R. C. Luo and M. G. Kay, Multisensor integration and fusion in intelligent systems, T-SMC 19, 1989,901-931. 1182. C. Brown, Gaze controls with interactions and delays, IUW, 200-218. 1183. K. Ikeuchi and J. C. Robert, Modeling sensor detectability with VANTAGE geometric/sensor modeler, IUW, 721-746. 1184. K. Tarabanis and R. Y. Tsai, Viewpoint planning: the visibility constraint, IUW, 893-903. 1185. T. S. Levitt and D. T. Lawton, Visual re-acquisition of geographic locations, IUW, 950-956. 1186. D. H. Graf and W. R. LaLonde, Neuroplanners and their application to eyes/head/neck coordination, IJCAI, 1022-1028. 1187. D. H. Ballard, Reference frames for animate vision, IJCAI, 1635-1641.
188-240 (1990)
SURVEY Image Analysis and Computer Vision: 1989” AZRIEL
ROSENFELD
Center for Automation Research, University of Maryland, College Park, Maryland 20742-3411
Received January lo,1990 This paper presents a bibliography of nearly 1200 references related to computer vision and image analysis, arranged by subject matter. The topics covered include architectures; computational techniques; feature detection, segmentation, and image analysis; matching, stereo, and time-varying imagery; shape and pattern; color and texture; and three-dimensional scene analysis. A few references are also given on related topics, such as computational geometry, computer graphics, image input/output and coding, image processing, optical processing, visual perception, neural nets, pattern recognition, and artificial intelligence. 0 1990 Academic Press, Inc.
1. INTRODUCTION
This is the twentieth in a series of bibliographies on computer processing of pictorial information, covering primarily items published during 1989. The coverage is restricted, for the most part, to a selected set of U.S. or international journals and proceedings of specialized meetings. No attempt is made to summarize or evaluate the items cited; the purpose is simply to provide a convenient compendium of references, grouped by subject. The references are arranged under the following headings: (A) (B) (0 (D) (E) (F) (G) (H) (I) (J)
General references Related topics Applications Architectures Computational techniques Feature detection, segmentation, image analysis Matching, stereo, time-varying imagery Shape and pattern Color and texture Three-dimensional scene analysis.
Letter/number codes in the text (A.l, etc.) correspond to sections of the bibliography. *The support of the Air Force Office of Scientific Research under Grant AFOSR-860092 is gratefully acknowledged, as is the help of Sandy German in preparing the bibliography. 188 0734-189X/90 $3.00 Copyright 0 1990 by Academic Press, Inc. All rights of reproduction in any form reserved.
IMAGE
ANALYSIS
AND
COMPUTER
VISION:
1989
189
Papers, books, etc. relating primarily to specific topics will be cited in later sections. In this section we cite references that relate to more than one topic: (A.0 Meetings and meeting proceedings [l-23] (A.2) Textbooks [24-261, a journal [27], some general papers 128-301,descriptions of research at various institutions [31-441, and the previous bibliography in this series [45]. 2. RELATED
TOPICS
The following related areas are not covered systematically, but we give a few references on them: (B.l) Computational geometry: Meetings, special issues, etc. [46-511. (B.2) Computer graphics: Meetings, etc. [52-631. (B.3) Image input/output [64-671, digitization [68-721, and coding [73-741. (B.4) Image processing (multidimensional signal processing, enhancement, restoration, reconstruction&general references [75-781, as well as papers on image smoothing [79-971 (see also [98]) and contrast enhancement [99-1011. (B.5) Optical processing [102-l 111. (B.6) Visual perception: meetings [112-1141, as well as a few books [115-1221 and papers [123-1261. (A few other papers on specific aspects of perception are cited in later sections.) (B.7) Neural networks, connectionism 2127-1531(see also [154-1561 on learning). (B.8) Pattern recognition and artificial intelligence: some general references [157-1691, as well as some papers on constraint satisfaction and relaxation methods [170-1761. 3. APPLICATIONS*
(C.l) Character recognition, document processing [ 177- 1781. (C.2) Biomedical applications [179-1831. CC.31Industrial applications [184-1961, including some general references on robotics applications [197-2001. (C.4) Autonomous systems [201-2061 (robot navigation, etc.), including some individual papers [207-2191. (C.5) Remote sensing, reconnaissance [220-2271, including some individual papers [228-2411. (C.6) Other applications [242-2431. 4. ARCHITECTURES
CD.11 General references [244-2571. (D.2) Meshes, hypercubes, etc. [258-2751. *Individual
papers on most of these topics are no longer cited in this bibliography.
190
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(D.3) Other systems [276-3011. (D.4) Related topics [301-3091. 5. COMPUTATIONAL
TECHNIQUES
(E.l) Image operations (convolutions, morphological operations, etc.) [310-3281. (E.2) Multiresolution and scale space methods [329-3421. (E.3) Geometric transformations, calibration [343-3621. (E.4) Interpolation, function fitting, etc. [363-3991 (see also [400-4021). 6. FEATURE
DETECTION,
SEGMENTATION,
AND
IMAGE
ANALYSIS
(F.l) Feature detection [403-4381. (F.2) Segmentation [439-4741. (F.3) Image analysis [475-4931. See also [494-5051 on geometry theorem proving and [506-5101 on grammars and automata, as well as [511-5121. 7. MATCHING,
STEREO,
AND
MOTION
(G.l) Image, template, and shape matching [513-5371; see also [538-5511 on Hough transforms, and [552-5661 on string, array, tree, graph, and point pattern matching. (G.2) Stereo 1567-5951. (G.3) Motion [596-7171 (see also [718-7261 on motion perception). 8. SHAPE
(H.l) Representations [727-7371; topology [738-7511. See also [752-7571 on geometric precision. (H.2) Lines and curves [758-7771 (see also [778-7801). (H.3) Distance and skeletons 1781-8061. (H.4) Properties and recognition [807-8321 (see also [833-8351X (H.5) Motion and path planning [836-8681; see also [869] on labyrinth searching, and [870-8771 on map building and learning. 9. COLOR
(1.1) (1.2) (1.3) (1.4)
AND
TEXTURE
Illumination and color [878-8881. Texture: models, synthesis [889-9101. Texture: description [911-9181. Texture: segmentation [919-9291. 10. THREE-DIMENSIONAL
SCENE ANALYSIS
(J.l) 3D data acquisition [930-9481 and analysis (feature detection, segmentation, property measurement) [949-9571; see also [958-9591 on 3D images and [960-9651 on grasping and machining. (5.2) Inference of 3D data from images (“recovery”) [966-10151.
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(5.3) 3D shape and models (surfaces and solids) [1016-10771; physically-based models [1078-10871 (see also [1088]>. (5.4) Image synthesis [1089-11271 (see also 111281). (J.5) 3D object recognition [1129-11661. (5.6) M iscellaneous topics (multisensor systems, sensor control, etc.) [1167-11871. REFERENCES
For brevity, the following frequently cited sources are cited in abbreviated forms: A. Conference Proceedings Abbreviation
Conference
AAAI CG CVPR IJCAI IUW SIGGRAPH WI3DS WVM
National Conference on Artificial Intelligence Symposium on Computational Geometry Conference on Computer Vision and Pattern Recognition International Joint Conference on Artificial Intelligence Image Understanding Workshop SIGGRAPH’89 Conference Workshop on Interpretation of Three-Dimensional Scenes Workshop on Visual Motion
Abbreviation
Journal
AI BC C&G CGA CVGIP DCG IJCV IJPRAI
Artificial Intelligence Biological Cybernetics Computers and Graphics IEEE Computer Graphics and Applications Computer Vision, Graphics, and Image Processing Discrete and Computational Geometry International Journal of Computer Vision International Journal of Pattern Recognition and Artificial Intelligence International Journal of Robotics Research Information Processing Letters Image and Vision Computing Journal of Computer and System Sciences Journal of the Optical Society of America Journal of Parallel and Distributed Computing Machine Vision and Applications Parallel Computing Proceedings of the IEEE Pattern Recognition Pattern Recognition Letters SIAM Journal on Computing Signal Processing IEEE Transactions on Acoustics, Speech, and Signal Processing IEEE Transactions on Computers
B. Journals
IJRR IPL IVC JCSS JOSA JPDC MVA PC P-IEEE PR PRL SIAM JC SP T-ASSP T-COMP
192
AZRIEL T-PAM1 T-RA T-SMC TCS TOG VC
ROSENFELD
IEEE Transactions on Intelligence IEEE Transactions on IEEE Transactions on Theoretical Computer ACM Transactions on The Visual Computer
Pattern Analysis and Machine Robotics and Automation Systems, Man, and Cybernetics Science Graphics
A. General References A. 1. Meetings 1. A. Krzyzak, T. Kasvand, and C. Y. Suen, eds., Computer vision and Shape Recognition (Vision Interface 88, Edmonton, Alberta, June 6-10, 1988), World Scientific, Singapore, 1989. 2. J. C. Simon, ed., From Pixels to Features (Proceedings of a workshop held in Bonas, France, August 22-27, 19881, North-Holland, Amsterdam, 1989. 3. Special Issue: 4th Alvey Vision Conference (Manchester, UK, August 31-September 2, 19881, NC 7 cl), February 1989,3-78. 4. Multi-site Seminar in Vision, Tel Aviv, Israel, March 17, 1989. 5. Proceedings, Image Understanding Workshop (Palo Alto, CA, May 23-26, 1989), Morgan Kaufmann, San Mateo, CA. 6. Proceedings, CVPR’89 (IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Diego, CA, June 4-8, 19891, Computer Society Press, Washington, DC. 7. Image Understanding and Machine Vision (Optical Society of America Topical Meeting, North Falmouth, MA, June 12-14, 1989), Optical Society of America, Washington, DC. 8. M. Pietiklinen and J. Rohning, eds., Proceedings of the 6th Scandinavian Conference on Image Analysis (Oulu, Finland, June 19-22, 19891, Pattern Recognition Society of Finland, 1989. 9. IBM Europe Institute on Common Topics in Image Analysis and Synthesis, Garmisch-Partenkirchen, FRG, July 10-14, 1989. 10. Third International Conference on Image Processing and its Applications (Warwick, UK, July 18-20, 1989), Institution of Electrical Engineers, London, UK, 1989. 11. Active Perception and Robot Vision (NATO Advanced Study Institute), Maratea, Italy, July 17-28, 1989. 12. A. G. Tescher, ed., Applications of Digital Image Processing XII (San Diego, CA, August 8-11, 1989), l+oc. SPIE 1153. 13. CAIP’89, Third International Conference on Computer Analysis of Images and Patterns, Leipzig, DDR, August 31-September 2, 1989. 14. From Pixels to Features (COST 13 Summer School), Bonas, France, September 4-9, 1989. 15. ICIP’89, IEEE International Conference on Image Processing, Singapore, September 5-8, 1989. 16. SICIAP, 5th International Conference on Image Analysis and Processing, Positano, Italy, September 20-22, 1989. 17. ASOIZ’89, Third Conference on Automated Systems of Image Processing, Leningrad, USSR, September 24-27, 1989. 18. AIPR, 18th Workshop on Applied Imagery Pattern Recognition, Washington, DC, October 11-13, 1989. 19. D. Casasent, ed., Intelligent Robots and Computer Vision VIII: Algorithms and Techniques (Philadelphia, PA, November 6-10, 19891, Proc. SPIE 1192. 20. B. G. Batchelor, ed., Intelligent Robots and Computer Vision VIII: Systems and Applications (Philadelphia, PA, November 9-10, 19891, Proc. SPZE 1193. 21. P. S. Schenker, ed, Sensor Fusion II: Human and Machine Strategies (Philadelphia, PA, November 6-9, 1989), Proc. SPZE 1198. 22. W. A. Pearlman, ed., Visual Communications and Image Processing IV (Philadelphia, PA, November S-10, 19891, Proc. SPZE 1199. 23. Proceedings, Workshop on Interpretation of 3D Scenes (Austin, TX, November 27-29, 1989), Computer Society Press, Washington, DC.
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A.2. Books, etc. 24. M. C. Fairhurst, Computer Vision for Robotic Systems-An Introduction, Prentice Hall, New York, 1988. 25. A. K. Jain, Fundamentals of Digital Image Processing, Prentice Hall, Englewood Cliffs, NJ, 1989. 26. R. J. Schalkoff, Digital Image Processing and Computer Vkion, Wiley, New York, 1989. 27. G. Wade, E. A. Robinson, and H. Lee, eds., International Journal of Imaging Systems and Technology, Wiley, New York, 1989ff. 28. J. R. Kender, Some issues for the panel on methodology and standards in CVPR research. CVPR, 436. 29. R. M. Haralick, Methodology for experimental computer vision, CVPR, 437-438. 30. D. Petkovic, The need for accuracy verification of machine vision algorithms and systems, CVPR. 439-440.
31. R. L. Simpson, An update on strategic computing computer vision, IUW, l-11. 32. M. A. Fischler and R. C. Belles, Image understanding research at SRI International, IUW, 21-31. 33. T. Kanade and S. Shafer, Image understanding research at Carnegie Mellon, IUW, 32-47. 34. A.R. Hanson and E. M. Riseman, Progress in computer vision at the University of Massachusetts, IUW, 49-55. 35. T. Poggio and the staff, MIT progress in understanding images, IUW, 56-74. 36. R. Nevatia, K. Price, and G. Medioni, USC image understanding research: 1988-89, IUW. 75-93. 37. A. Rosenfeld, L. S. Davis, and J. (Y.) Aloimonos, Image understanding research at the University
of Maryland (January 1988-February 19891,IUW, 94-109. 38. J. R. Kender, P. K. Allen, and T. E. Boult, Image understanding and robotics research at Columbia University, IUW, 110-121. 39. C. M. Brown and R. C. Nelson, Image understanding at the University of Rochester, IUW. 122-127. 40. N. R. Corby, Image understanding research at GE, IUW, 144-146. 41. C. Bjorklund, M. Noga, E. Barrett, and D. Kuan, Lockheed imaging technology research for missiles and space, IUW, 332-352. 42. R. M. Bolle, A. Califano, R. Kjeldsen, and R. W. Taylor, Computer vision research at the IBM T. J. Watson Research Center, IUW, 471-478. 43. E. M. Riseman and A. R. Hanson, Computer vision research at the University of Massachusetts -themes and progress, IJCV 2, 1989, 199-207. 44. M. A. Fischler, An overview of computer vision research at SRI International-themes and progress, IJCV 3, 1989, 7-15. 45. A. Rosenfeld, Image analysis and computer vision: 1988, CVGIP 46, 1989, 196-264.
B. Related Topics B.l. Computation Geometry 46. H. Noltemeier, ed., Computational Geometry and its Applications, Springer, Berlin, 1988. 47. Proceedings of the Fifth Annual Symposium on Computational Geometry (Saarbriicken, FRG. June 5-7, 19891,ACM Press, New York. 48. First Canadian Conference on Computational Geometry, Montreal, Quebec, August 21-25, 1989. 49. J. O’Rourke, The computational geometry column #3, Computer Graphics 23, 1989, 212-213. 50. C. K. Yap, guest ed., Special Issue on Computational Geometry, Algorithmica 4 (11, 1989, 1-155.
51. C. Yap, guest ed., Special Issues on Computational Geometry. JCSS 39 (2), October 1989, 125-241.
B.2. Computer Graphics 52. D. F. Rogers and R. A. Earnshaw, eds., Computer Graphic Techniques, Springer, Berlin, 1989. 53. NCGA’89 (Tenth Annual Conference and Exposition, National Computer Graphics Association). Philadelphia, PA, April 16-20, 1989. 54. Proceedings, Graphics Interface ‘89 (London, Ontario, June 19-23, 1989), Morgan Kaufmann, San Mateo, CA, 1989.
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55. N. Magnenat-Thalmann and D. Thalmann, eds., New Trends in Computer Graphics (Proceedings, Computer Graphics International ‘88, Geneva, Switzerland, May 24-27, 19881, Springer, Berlin, 1988. 56. N. Magnenat-Thalmann and D. Thalmann, eds., Special Issue on Computer Graphics International ‘88 (CGI ‘88), VC 5 (l-21, 1989, 1-119. 57. R. A. Eamshaw and B. Wyvill, eds., New Advances in Computer Graphics (Proceedings, Computer Graphics International ‘89, 7th Conference of the Computer Graphics Society, Leeds, UK, June 27-30, 1989), Springer, Berlin, 1989. 58. SIGGRAPH’89 Conference Proceedings (Boston, MA, July 31-August 4, 1989), Compufer
B.3. Image I/O,
Digitization,
and Coding
64. R. R. Morton and R. C. Hsieh, eds., Imaging Workstations and Document Input Systems (Los Angeles, CA, January 17-20, 19891, Proc. SPIE 1074. 65. G. M. Nelson, guest ed., Visualization in Scientific Computing, Computer 22 (8), August 1989, 10-101. 66. Imaging ‘89 (Sixth Annual International Electronic Imaging ‘89 East Exposition and Conference), Boston, MA, October 2-5, 1989. 67. Imagexpo (International Imaging Industry Conference and Exposition), Vienna, Austria, October 18-20, 1989. 68. S. B. M. Bell, F. C. Holroyd, and D. C. Mason, A digital geometry for hexagonal pixels, NC 7, 1989, 194-204. 69. J. D. Hobby, Rasterizing curves of constant width, J. ACM 36, 1989, 209-229. 70. B. Kamgar-Parsi and B. Kamgar-Parsi, Evaluation of quantization error in computer vision, T-PAMI
11, 1989,929-940.
71. B. Kamgar-Parsi, B. Kamgar-Parsi, and W. A. Sander III, Quantization error in spatial sampling: comparison between square and hexagonal pixels, CVPR, 604-611. 72. N. Gharachorloo, S. Gupta, R. F. Sproull, and I. E. Sutherland, A characterization of ten rasterization techniques, SIGGRAPH, 355-368. 73. L. Chariglione, ed., Signal Processing: Image Communication-Theory, Techniques, and Applications, Elsevier, 1989ff. 74. H. G. Musmann, guest ed., Special Issue on 64kbit/s coding of moving video, Image Communication 1 (21, October 1989, 83-243.
B .4. Image Processing 75. J. Biemond, guest ed., Special Issue on Multidimensional Signal Processing (Part II), SP 16 (0, January 1989, l-82. 76. J. Duvemoy, ed., Image Processing III (Paris, France, April 24-28, 19891, Proc. SPIE 1135. 77. N. K. Bose, M. Simaan, and J. Biemond, eds., Multidimensional Systems and Signal Processing, Kluwer, 1990ff. 78. Sixth Workshop on Multidimensional Signal Processing, Monterey, CA, September 6-8, 1989. 79. S. J. Willson, Convergence of iterated median rules, CVGIP 47, 1989, 105-110. 80. P. W. Verbeek and B. J. H. VeMrer, 2-D adaptive smoothing by 3-D distance transformation, PRL 9, 1989, 53-65. 81. E. R. Davies, Edge location shifts produced by median filters: theoretical bounds and experimental results, SP 16, 1989, 83-96.
IMAGE ANALYSIS AND COMPUTER
VISION:
1989
19.5
82. F. Safa and G. Flouzat, Speckle removal on radar imagery based on arithmetical morphology, SP 16, 1989, 319-333. 83. J. Astola and Y. Neuvo, Optimal median type filters for exponential noise distributions, .SP 17. 1989, 9.5-104. 84. L. Naaman and A. C. Bovik, Least-squares order statistic filters with coefficient censoring, S P 18, 1989, 139-152. 85. R. Kutka, A variable median filter for image restoration adaptable to different types of spike noise, S P 18, 1989, 217-224. 86. H. U. Diihler, Generation of root signals of two dimensional median filters. S P 18, 1989. 269-276. 87. H. G. Longbotham and A. C. Bovik, Theory of order statistic filters and their relationship to linear FIR filters, T-ASSP 37, 1989, 275-287. 88. Y. H. Lee, S. J. Ko, and A. T. Fam, Efficient impulsive noise suppression via nonlinear recursive filtering, T-ASSP 37, 1989, 303-306. 89. J. T. Astola and T. G. Campbell, On computation of the running median, T-ASSP 37. 1989. 572-574. 90. F. Palmieri and C. G. Boncelet, Jr., Ll filters-a new class of order statistic filters, T-ASSP 37. 1989, 691-701. 91. S. Y. Park and Y. H. Lee, Double smoothing of images using median and Wiener filters, T-ASSP 37, 1989, 943-946. 92. A. Kundu and W. R. Wu, Double-window Hodges-Lehman (D) filter and hybrid D-median filter for robust image smoothing, T-ASSP 37, 1989, 1291-1298. 93. P. P. Gandhi, I. Song, and S. A. Kassam, Nonlinear smoothing filters based on rank estimates of location, T-ASSP 37, 1989, 1359-1379. 94. 0. Vainio, Y. Neuvo, and S. E. Butner, A signal processor for median-based algorithms, T-ASSP 37, 1989, 1406-1414. 95. C. Ray and R. K. Ward. A parametrized family of nonlinear image smoothing filters, T-ASSP 37, 1989, 1458-1462. 96. P. Saint-Marc, J. S. Chen, and G. Medioni, Adaptive smoothing: a general tool for early vision. CVPR, 618-624. 97. L. D. Cai, A “small leakage” model for diffusion smoothing of image data, IJCAI, 1585-1590. 98. J. M. Steele, Certifying smoothness of discrete functions and measuring legitimacy of images. J. Complexity 5, 1989, 261-270. 99. A. Beghdadi and A. Le Negrate, Contrast enhancement technique based on local detection of edges, CVGIP 46, 1989, 162-174. 100. K. W. Leszczynski and S. Shalev, A robust algorithm for contrast enhancement by local histogram modification. NC 7, 1989, 205-209. 101. H. Li and H. S. Yang, Fast and reliable image enhancement using fuzzy relaxation technique, T-SMC 19, 1989, 127661281.
B.5. Optical Processing 102. R. Arrathoon, Optical Computing-Digital and Symbolic, Dekker, New York, 1989. 103. H. K. Liu, ed.. Optical Pattern Recognition (Los Angeles, CA, January 17-18, 19891,Proc. SPIE 1053. 104. H. J. Caulfield, ed., Optical Pattern Recognition II (Paris, France, April 24-28, 1989), Proc. SPIE 1134. 105. B. Javidi, ed., Optical Information Processing Systems and Architectures (San Diego, CA, August 8-11, 19891,hoc. SPIE 1151. 106. J. L. Horner, guest ed., Special Section on Optical Devices and Computing, P-IEEE 77 (lo), October 1989, 1511-1583. 107. C. K. Campbell, Application of surface acoustic and shallow bulk acoustic wave devices, P-IEEE 77, 1989, 1453-1484. 108. D. L. Flannery and J. L. Horner, Fourier optical signal processors, P-IEEE 77, 1989, 1511-1527. 109. J. N. Lee and A. VanderLugt, Acoustooptic signal processing and computing, P-IEEE 77. 1989. 1.528-1557. 110. W. T. Cathey. K. Wagner, and W. J. Miceli, Digital computing with oplics, P-IEEE 77, 1989. 155881572.
196
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111. M. M. Eshaghian and V. K. Prasanna-Kumar, Fine grain image computations on electro-optical arrays, CVPR, 666-761.
8.6. Visual Perception 112. B. E. Rogowitz, ed., Human Vision, Visual Processing, and Digital Display (Los Angeles, CA, January 18-20, 1989), Proc. SPZE 1077. 113. Vision and Three-Dimensional Representation, Minneapolis, MN, May 24-26, 1989. 114. Workshop on Human and Machine Vision, North Falmouth, MA, June 15, 1989. 11.5. W. A. Richards, ed., Natural Computation, MIT Press, Cambridge, MA, 1988. 116. R. L. De Valois and K. K. De Valois, Spatiul I&ion, Oxford University Press, Oxford, UK 1988. 117. B. M. Bennett, D. D. Hoffman, and C. Prakash, Observer Mechanics-A Formul Theory of Perception, Academic Press, Orlando, FL, 1989. 118. M. L. Commons, R. J. Herrnstein, S. M. Kosslyn, and D. B. Mumford, eds., Behavioral Approaches to Pattern Recognition and Concept Formation, Erlbaum, Hillsdale, NJ, 1989. 119. M. Hershenson, The Moon Illusion-An Anomaly of Visaal Space Perception?, Erlbaum, Hillsdale, NJ, 1989. 120. G. Humphreys and V. Bruce, Visual Cognition: Computational, Experimentul, and Neuropsychologicul Perspectives, Erlbaum, Hillsdale, NJ, 1989. 121. B. E. Shepp and S. Ballesteros, Object Perception-Structure and Process, Erlbaum, Hillsdale, NJ, 1989. 122. R. A. Finke, Principles of Mental Imagery, MIT Press, Cambridge, MA, 1989. 123. J. B. Deregowski, Real space and represented space: cross-cultural perspectives, Behavioral Bruin Sciences 12, 1989, 51-119. 124. D. H. Ballard, Behavioural constraints on animate vision, ZVC 7, 1989, 3-9. 125. R. J. Watt, Scanning from coarse to fine spatial scales in the human visual system after the onset of a stimulus, JOSA A4, 1987, 2006-2021. 126. Z. Xie and T. G. Stockham, Jr., Toward the unification of three visual laws and two visual models in brightness perception, T-SMC 19, 1989, 379-387.
B.7. Neural Networks 127. E. R. Caianiello, ed., Parallel Architectares and Neural Networks (First Italian Workshop, Salerno, Italy, April 27-29, 1988), World Scientific, Singapore, 1989. 128. IJCNN’89, International Joint Conference on Neural Networks, Washington, DC, June 18-22, 1989. 129. Neuro-Nimes ‘89, Second International Workshop on Neural Networks and their Applications, Nimes, France, November 13-16, 1989. 130. V. Vemuri, ed., Arttjkiul Neural Networks: Theoretical Concepts, Computer Science Press, Rockville, MD, 1988. Synapses to Networks, MIT 131. C. Koch and I. Segev, eds., Methods in Neuronal Modeling-From Press, Cambridge, MA, 1988. 132. S. Pinker and J. Mehler, eds., Connections and Symbols, MIT Press, Cambridge, MA, 1988. 133. C. C. Klimasauskas, A Bibliography of Neurocomputing, MIT Press, Cambridge, MA, 1988. 134. R. E&miller and C. v. d. Malsburg, eds., Neural Computers, Springer, Berlin, 1988. 135. Y. H. Pao, Adaptive Pattern Recognition and Neural Networks, Addison-Wesley, Reading, MA, 1989. 136. M. A. Gluck and D. E. Rumelhart, eds., Neuroscience and Connectionist Theory, Erlbaum, Hillsdale, NJ, 1989. 137. I. Aleksander, ed., Neural Computing Architectures, MIT Press, Cambridge, MA, 1989. 138. S. J. Hanson and C. R. Olson, eds, Connectionist Modeling and Bruin Function-The Developing btterface, MIT Press, Cambridge, MA, 1989. 139. L. Nadel, ed., Neural Connections, Mental Computation, MIT Press, Cambridge, MA, 1989. 140. C. C. Klimasauskas, The 1989 Neuro-Computing Bibliography, MIT Press, Cambridge, MA, 1989. 141. R. Pfeifer, Z. Schreter, F. Fogelman-Soulie, and L. Steels, eds., Connectionism in Perspective, North-Holland, Amsterdam, 1989. 142. P. Wasserman, Neural Computing-Theory and Applications, Van Nostrand, New York, 1989. 143. S. Brunak and B. Lautrup, Neural Networks-Computers with Intuition, World Scientific, Singapore, 1989.
IMAGE ANALYSIS AND COMPUTER
VISION:
1989
197
144. B. Lautrup, The Hopjield Model, World Scientific, Singapore, 1989. 145. C. A. Will, ed., The Neural Network Review, Erlbaum, 1987ff. 146. H. Szu, ed., Journal of Neural Network Computing-Technology, Design, and Applications. Auerbach, 1989ff. 147. B. Lautrup and S. BNIK&, eds., International Journal of Neural Systems, World Scientific, 1989ff. in Neural Systems, American Institute of Physics, 148. D. J. Amit, ed., NETWORK-Computation 199off.
149. G. Buchsbaum and W. Freedman, guest eds., Special Issue on Neurosystems and Neuroengineering, IEEE Trans. Biomedical Engineeting 36 cl), January 1989, 2-160. 150. M. A. Arbib, guest ed., Special Issue: Neural Computing, JPDC 6 (21, April 1989, 183-449. 151. G. E. Hinton, Connectionist learning procedures, AI 40, 1989, 185-234. 152. H. J. Caulfield, J. Kinser, and S. K. Rogers, Optical neural networks, P-IEEE 77, 1989, 1573-1583. 153. E. Saund, Dimensionality-reduction using connectionist networks, T-PAMI 11, 1989, 304-314. 154. D. Haussler and L. Pitt, eds., Proceedings of the 1988 Workshop on Computational Learning Theory, Morgan Kaufmann, San Mateo, CA, 1988. 155. R. Forsyth, ed., Machine Learning--Principles and Techniques, Chapman and Hall, New York, 1989.
156. J. G. Carbonell, guest ed., Special Volume on Machine Learning, AI 40 (l-3), September 1989, l-385.
B.8. Pattern Recognition,
Artificial
Intelligence
157. N. G. Zagoruiko, guest ed., Proceedings of the International Workshop on Expert Systems and Pattern Recognition (ESPR) (Novosibirsk, USSR, October 26-29, 1987), IJPRAI 3 (1). March 1989, 1-157. 158. G. Ferrate et al., eds., Syntactic and Structural Pattern Recognition, Springer, Berlin, 1988. 159. J. Kittler, ed., Pattern Recognition, Springer, Berlin, 1988. 160. T. O’Shea and V. Sgurev, eds., Artificial Intelligence III-Methodology, Systems, Applications (Proceedings of the Third International Conference, AIMSA ‘88, Varna, Bulgaria, September 20-23, 19881,North-Holland, Amsterdam, 1988. 161. Fifth IEEE Conference on Artificial Intelligence Applications, Miami, FL, March 6-10, 1989. 162. M. M. Trivedi, ed., Applications of Artificial Intelligence VII (Orlando, FL, March 28-30, 1989). Proc. SPIE 1095.
163. IJCAI’89, Eleventh International Joint Conference on Artificial Intelligence, Detroit, MI, August 20-25, 1989.
164. A. G. Cohn, ed., AISB’89, Morgan Kaufmann, San Mateo, CA, 1989 165. M. Pavel, Fundamentals of Pattern Recognition, Dekker, New York, 1988. 166. C. W. Therrien, Decision Estimation and Classification-An Introduction to Pattern Recognition and Related Topics, Wiley, New York, 1989. 167. S. R. Graubard, ed., The Artijicial Intelligence Debate, MIT Press, Cambridge, MA, 1988. 168. M. Sharples, D. Hogg, C. Hutchison, S. Torrance, and D. Young, eds., Computers and Thought-A Practical Introduction to Artificial Intelligence, MIT Press, Cambridge, MA, 1989. 169. D. W. Bouldin, guest ed., Special Section on Advanced Systems Architectures for Artificial Intelligence, T-SMC 19 (4), July-August 1989, 665-713. 170. M. J. Swain, Comments on Samal and Henderson: “Parallel consistent labeling algorithms,” Intl. J. Parallel Programming 17, 1988, 523-528. 171. J. Kittler and E. R. Hancock, Combining evidence in probabilistic relaxation, IJPRAI 3, 1989, 29-51.
172. R. Bodington, G. D. Sullivan, and K. D. Baker, Consistent labelling of image features using an assumption-based truth maintenance system, n/C 7, 1989, 43-49. 173. J. S. Duncan and W. Frei, Relaxation labeling using continuous label sets, PRL 9, 1989, 27-37. 174. P. Parent and S. W. Zucker, Radial projection: an efficient update rule for relaxation labeling, T-PAMI 11, 1989, 886-889.
175. X. Zhuang, R. M. Haralick, and H. Joo, A simplex-like algorithm for the relaxation labeling process, T-PAMI 11, 1989, 1316-1321. 176. M. J. Swain and P. R. Cooper, Parallel hardware for constraint satisfaction, AAAI, 682-686.
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C. Applications C.1. Document
Processing
177. G. P. Herring and V. A. Uzilevsky, eds., International Journal of Research and Engineering-Postal Applications, 1989tf. 178. R. Suchenwirth, J. Guo, I. Hartmann, G. Hincha, M. Krause, and Z. Zhang, Optical Recognition of Chinese Characters, Vieweg, Berlin, 1989.
C.2. Biomedical Applications 179. V. L. Newhouse, ed., Progress in Medical Imaging, Springer, Berlin, 1988. 180. M. A. Viergever and A. Todd-Pokropek, eds., Mathematics and Computer Science in Medical Imaging, Springer, Berlin, 1988. 181. S. J. Dwyer III, R. G. Jost, and R. H. Schneider, eds., Medical Imaging III (Newport Beach, CA, 1989): Image Formation (January 29-311, Proc. SPZE 1090, Image Capture and Display (January 29-31), Proc. SPZE 1090, Image Processing (January 31-February 3), Proc. SPIE 1092; PACS System Design and Evaluation (January 31-February 3), Proc. SPZE 1093. 182. M. A. Viergever, ed., Science and Engineering of Medical Imaging (Paris, France, April 24-28, 19891, Proc. SPIE 1137. 183. R. A. Bauman, ed., Journal of Digital Imaging (Society for Computer Applications in Radiology), Saunders, 1988ff.
C.3. Industrial
Applications
184. H. Freeman, ed., Machine Vision for Inspection and Measurement (Second Annual Machine Vision Workshop, New Brunswick, NJ, April 25-26, 19881,Academic Press, Orlando, FL, 1989. 185. Third Annual Machine Vision Workshop, New Brunswick, NJ, April 3-4, 1989. 186. IEEE International Workshop on Industrial Applications of Machine Intelligence and Vision (MIV-891, Tokyo, Japan, April 10-12, 1989. 187. Vision ‘89 (Society of Manufacturing Engineers), Rosemont, IL, April 24-27, 1989. 188. Ident/Vision (2nd International Conference on Applied Vision and Artificial Intelligence and 3rd International Conference on Automatic Identification and Sensors); ROVISEC (8th International Conference on Robot Vision and Sensory Control); AIPC (9th International Conference on Automated Inspection and Product Control), Stuttgart, FRG, May 30-June 1, 1989. 189. D. J. Svetkoff, ed., Optics, Illumination, and Sensing for Machine Vision (Philadelphia, PA, November 8-10, 19891, Proc. SPIE 1194. 190. M. J. W .Chen, ed., Automated Inspection and High Speed Vision Architectures (Philadelphia, PA, November 6-7, 19891, Proc. SPIE 1197. 191. J. L. C. Sanz, Advances in Machine Vision, Springer, Berlin, 1988. 192. L. F. Pau, Computer Vision for Electronics Manufacturing, Plenum, New York, 1989. 193. J. Encarnacao and U. Rembold, guest eds., Graphics for Robotics and CAD/CAM/CIM Planning, CGA 9 (11, January 1989, 14-74. 194. C. T. Wilfong, guest ed., Robotics and Automation, Computer 22 (31, March 1989, 6-60. 195. A. J. Koivo, W. A. Gruver, C. P. Neuman, H. E. Stephanou, and L. W. Stark, eds., Special Section on Information Technology for Sensory-Based Robot Manipulators, T-SMC 19 (4), July-August, 1989, 780-860. 196. A. Kusiak, ed., Journal of Intelligent Manufacturing, Chapman and Hall, 199Off. 197. G. Rodriguez, ed., Intelligent Control and Adaptive Systems (Philadelphia, PA, November 7-8, 19891, Proc. SPZE 1196. 198. 0. Khatib, J. J. Craig, and T. Lozano-Perez, eds., The Robotics Review I MIT Press, Cambridge, MA, 1989. 199. J. M. Brady, ed., Special Issue on Sensor Data Fusion, ZJRR 7 (61, December 1988, 1-161. 200. V. J. Lumelsky and R. A. Brooks, eds., Special Issue on Sensor-Based Planning and Control in Robotics, T-JU 5 (61, December 1989, 713-825.
C.4. Autonomous
Systems
201. A. G. Gale, M. H. Freeman, C. M. Haslegrave, P. Smith, and S. P. Taylor, eds., Vision in Vehicles 11 (Nottingham, UK, September 14-17, 19871,North-Holland, Amsterdam, 1988. 202. Mini-Symposium on Robot Navigation, Stanford, CA, March 28-30, 1989.
IMAGE ANALYSIS AND COMPUTER
VISION: 1989
199
203. International Workshop on Visual Information Processing for Television and Telerobotics. Williamsburg, VA, May 10-12, 1989. 204. SITEF 89, Research Trends and Application Impacts of Machine and Systems Intelligence. Tolouse, France, October 18-19, 1989. 205. W. J. Wolfe, ed., Mobile Robots IV (Philadelphia, PA, November 6-7, 19891, Proc. SPIE 1195. 206. International Conference on Intelligent Autonomous Systems, Amsterdam, The Netherlands. December 11-14, 1989. 207. S. S. Iyengar and R. L. Kashyap, guest eds., Autonomous Intelligent Machines, Computer 22 (6). June 1989, 14-97. 208. J. Bares, M. Hebert, T. Kanade, E. Krotkov, T. Mitchell, R. Simmons, and W. Whittaker. Ambler -an autonomous rover for planetary exploration, Computer 22 (61, 1989, 18-26. 209. C. R. Weisbin, G. de Saussure, J. R. Einstein, F. G. Pin, and E. Heer. Autonomous mobile robot navigation and learning, Computer 22 (6), 1989, 29-3.5. 210. N. S. V. Rao, Algorithmic framework for learned robot navigation in unknown terrains, Compute! 22 (6), 1980, 37-43. 211. A. M. Flynn, Combining sonar and infrared sensors for mobile robot navigation, IJRR 7 (6). 1988. 5-14. 212. U. K. Sharma and D. Kuan, Real-time model based geometric reasoning for vision-guided navigation, MVA 2, 1989, 31-44. 213. D. J. Kriegman, E. Triendl, and T. 0. Binford, Stereo vision and navigation in buildings for mobile robots, T-RA 5, 1989, 792-804. 214. D. T. Lawton and T. S. Levitt, Knowledge based vision for terrestrial robots, IUW, 128-133. 215. K. E. Olin, M. J. Daily, J. G. Harris, and F. M. Vilnrotter, Knowledge-based vision technology overview for obstacle detection and avoidance, IUW, 134-143. 216. C. Fennema, A. Hanson, and E. Riseman, Towards autonomous mobile robot navigation, IUW. 219-231. 217. C. Thorpe and T. Kanade, Carnegie Mellon Navlab Vision, IUW, 273-282. 218. D. P. Miller, R. Brooks, R. Chatila, S. Harmon, S. Rosenschein, C. Thorpe, and C. Weisbin. Robot navigation, IJCAI, 1672-1674. 219. J. J. Rodriguez and J. K. Aggarwal, Navigation using image sequence analysis and 3-D terrain matching, WISDS, 200-207.
C.5. Remote Sensing, Reconnaissance 220. I. Hirschberg, ed., Reconnaissance, Astronomy, Remote Sensing, and Photogrammetry (Lox Angeles, CA, January 19-20, 19891,Proc. SPZE 1070. 221. 0. E. Drummond, ed., Digital Signal Processing, Association and Tracking of Point Source. Small and Cluster Targets (Orlando, FL, March 27-29, 1989), Proc. SPZE 1096. 222. M. R. Weathersby, ed., Aerospace Pattern Recognition (Orlando, FL, March 30-31, 1989), Proc. SPIE 1098.
223. A. G. Tescher, ed., Advances in Image Compression and Automatic Target Recognition (Orlando. FL, March 30-31, 1989), Proc. SPZE 1099. 224. C. Weaver, ed., Sensor Fusion II (Orlando, FL, March 28-29, 1989), Proc. SPZE 1100. 225. A. J. Huber, ed., Imaging Infrared: Scene Simulation and Real Image Tracking (Orlando, FL, March 30-31, 1989), Proc. SPZE 1110. 226. G. Duchossois, F. L. Herr, and R. Zander, eds., Advanced Optical Instrumentation for Remote Sensing of the Earth’s Surface from Space (Paris, France, April 24-28, 1989), Proc. SPIE 1129. 227. P. A. Hendel, F. R. LaGesse, W. W. Schurter, T. W. Augustyn and T. G. Shepherd, eds., Airborne Reconnaissance XIII (San Diego, CA, August 7-9, 1989), Proc. SPIE 1156. 228. D. M. McKeown, Jr., W. A. Harvey, and L. E. Wixson, Automating knowledge acquisition for aerial image interpretation, CVGZP 46, 1989, 37-81. 229. W. W. SeemuIIer, The extraction of ordered vector drainage networks from elevation data. CVGIP 47, 1989, 48-58.
230. M. G. Thomason, Knowledge-based analysis of satellite oceanographic images, Id. J. Intelligenf Systems 4, 1989, 143-154. 231. D. C. Baker, S. S. Hwang, and J. K. Aggarwal, Detection and segmentation of man-made objects in outdoor scenes: concrete bridges, JOSA A6, 1989, 938-950.
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232. V. Roberto and A. Peron, Low-level processing techniques in geophysical image interpretation, PRL 10, 1989, 111-122. 233. M. E. Bernard, Detection of airborne compact sources in infra-red scenes using syntactic pattern recognition, PRL. 10, 1989, 123-126. 234. B. Bhanu, Understanding scene dynamics, IUW, 147-164. 235. G. .I. Ettinger and T. S. Levitt, An intelligent tactical target screener, IUW, 283-297. 236. J. F. Bogdanowicz and A. Newman, Overview of the SCORPIUS program, IUW, 298-308. 237. D. E. Dudgeon, J. G. Verly, and R. L. Delaney, An experimental target recognition system for laser radar imagery, IUW, 479-506. 238. P. Fua and A. J. Hanson, Objective functions for feature discrimination: applications to semiautomated and automated feature extraction, IUW, 676-694. 239. M. A. Fischler and T. M. Strat, Recognizing objects in a natural environment: a contextual vision system (CVC), IUW, 774-796. 240. K. Kaneda, F. Kato, E. Nakamae, T. Nishita, H. Tanaka, and T. Noguchi, Three-dimensional terrain modeling and display for environmental assessment, SIGGRAPH, 207-214. 241. A. Huertas, W. Cole, and R. Nevatia, Using generic knowledge in analysis of aerial scenes: a case study, IJCAI, 1642-1648.
C.6. Other Applications 242. H. T. A. Whiting, ed., Human Movement Science, North-Holland, 1982ff. 243. A. W. Young and H. D. Ellis, eds., Handbook of Research on Face Processing, North-Holland, Amsterdam, 1989.
D. Architectures D. 1. General References 244. M. Cosnard, M. H. Barton, and M. Vanneschi, eds., Parallel Processing (IFIP Working Group, Pisa, Italy, April 25-27, 1988), North-Holland, Amsterdam, 1988. 245. W. E. Nagel, 1988 International Conference on Supercomputing, PC 9, 1988-9, 117-118. 246. J. F. Hake and R. J. Van der Pas, The 2nd International Conference on Vector and Parallel Computing: Issues in Applied Research and Development, PC 9, 1988-9, 119-122. 247. R. Mills, ed., Proceedings, The 2nd Symposium on the Frontiers of Massively Parallel Computation (Fairfax, VA, October 10-12, 1988), Computer Society Press, Washington, DC, 1988. 248. International Conference on Systolic Arrays, Killamey, Ireland, May 31-June 2, 1989. 249. ACM Symposium on Parallel Algorithms and Architectures, Santa Fe, NM, June 18-21, 1989. 250. International Conference on Parallel Processing, St. Charles, IL, August 8-12, 1989. 251. Parallel Computing 89, Leiden, The Netherlands, August 29-September 1, 1989. 252. C. R. Dyer, ed., Special Section on Computer Architectures and Parallel Algorithms for PAM1 (Papers presented at the Workshop on Computer Architecture for Pattern Analysis and Machine Intelligence, Seattle, WA, October 5-7, 1987), T-PAMI 11 (3), March 1989, 225-265. 253. J. L. C. Sanz, ed., Position papers presented at the panel: Which parallel architectures are useful/useless for vision algorithms, WA 2, 1989, 167-173. 254. D. Gannon, A. Lichewsky, Y. Muraoka, and A. Sameh, eds., International Journal of High Speed Computing, World Scientific, 1989tI. 255. S. G. Akl, The Design and Analysis of Parallel Algorithms, Prentice-Hall, Englewood Cliffs, NJ, 1989. 256. K. Preston, Jr., The Abingdon Cross benchmark survey, Computer 22 (71, 1989, 9-18. 257. C. Weems, E. Riseman, A. Hanson, and A. Rosenfeld, A report on the results of the DARPA Integrated Image Understanding Benchmark Exercise, IUW, 165-192.
0.2.
Meshes, Hypercubes, etc.
258. H. Simon, ed., Scientific Applications of the Connection Machine (Mountainview, CA, September 12-14, 19881,World Scientific, Singapore, 1989. 259. S. Ranka and S. Sahni, Hypercube Algotithms for Image Processing and Pattern Recognition, Springer, Berlin, 1989. 260. W. D. Gropp and I. C. F. Ipsen, Recursive mesh refinement on hypercubes, BIT 29, 1989, 186-211.
IMAGE ANALYSIS AND COMPUTER
VISION: 1989
201
261. F. Ozguner and C. Aykanat, A reconfiguration algorithm for fault tolerance in a hypercube multiprocessor, IPL 29, 1988, 247-254. 262. A. M. Gibbons and Y. N. Srikant, A class of problems efficiently solvable on mesh-connected computers including dynamic expression evaluation, IPL 32, 1989, 305-311. 263. V. Di Gesu, An overview of pyramid machines for image processing, IS 47, 1989, 17-34. 264. I. D. Scherson, S. Sen, and Y. Ma, Two nearly optimal sorting algorithms for mesh-connected processor arrays using shear-sort, JPDC 6, 1989, 1.51-16.5. 265. T. Bier and K. F. Lee, Embedding of binary trees into hypercubes, JPDC 6, 1989, 679-691. 266. A. Wagner, Embedding arbitrary binary trees in a hypercube, JPDC 7, 1989, 503-520. 267. L. Boxer and R. Miller, Dynamic computational geometry on meshes and hypercubes. J. Supercomputing 3, 1989, 161-191. 268. J. P. Sheu, C. L. Wu, and G. H. Chen, Selection of the first k largest processes in hypercubes. PC 11, 1989, 381-384. 269. M. S. Chen and K. G. Shin, On relaxed squashed embedding of graphs into a hypercube, SIAM JC 18, 1989, 1226-1244. 270. I. D. Scherson and S. Sen, Parallel sorting in two-dimensional VLSI models of computation, T-COMP 38, 1989, 238-249. 271. R. Miller and Q. F. Stout, Mesh computer algorithms for computational geometry, T-COMP 38, 1989, 321-340. 272. H. G. Badr and S. Podar, An optimal shortest-path routing policy for network computers with regular mesh-connected topologies, T-COMP 38, 1989, 1362-1371. 273. G. E. Blelloch, Scans a primitive parallel operations, T-COMP 38, 1989, 1.520-1538. 274. J. J. Little, G. E. BIelIoch, and T. A. Cass, Algorithmic techniques for computer vision on a fine-grained parallel machine, T-PAMI 11, 1989, 244-257. 275. V. K. Prasanna-Kumar and D. I. Reisis, Image computations on meshes with multiple broadcast. T-PAMI 11, 1989, 1194-1202.
0.3.
Other Systems
276. R. Bakalash and A. Kaufman, Medicube: a 3D medical imaging architecture, C&G 13, 1989. 151-157. 277. H. Umeo and T. Asano, Systolic algorithms for computational geometry problems-a survey, Computing 41, 1989, 19-40. 278. L. S. Dreschler-Fischer and H. Faasch, A kernel system for iconic image processing, Comprdting 42, 1989, 91-108. 279. L. G. C. Hamey, J. A. Webb, and I. C. Wu, An architecture independent programming language for low-level vision, CVGIP 48, 1989, 246-264. 280. R. S. Wallace, J. A. Webb, and I. C. Wu, Machine-independent image processing: performance of Apply on diverse architectures, CVGIP 48, 1989, 265-276. 281. C. C. Weems, S. P. Levitan, A. R. Hanson, and E. M. Riseman, The Image Understanding Architecture, N W 2, 1989, 251-282. 282. 0. H. Ibarra and T. Jiang. Optimal simulation of tree arrays by linear arrays, IPL 30, 1989. 295-302. 283. P. W. Pachowicz, Image processing by software parallel computation, W C 7, 1989, 122-128. 284. A. W. G. Duller, R. H. Storer, A. R. Thomson, and E. L. Dagless, An associative processor array for image processing, IVC 7, 1989, 151-158. 285. 0. H. Ibarra, T. Jiang, and J. H. Chang, On iterative and cellular tree arrays, JCSS 38, 1989. 452-473. 286. C. H. Chu, E. J. Delp, L. H. Jamieson, H. J. Siegel, and F. J. Weil, A model for an intelligent operation system for executing image understanding tasks on a reconfigurable parallel architecture, JPDC 6, 1989, 598-622. 287. A. Rosenfeld, Arc colorings, partial path groups, and parallel graph contractions, JPDC 7, 1989. 335-354. 288. M. Maresca, H. Li, and M. M. C. Sheng, Parallel computer vision on polymorphic torus architecture, W A 2, 1989, 215-230. 289. E. H. L. Aarts and J. H. M. Korst, Computations in massively parallel networks based on the Boltzmann machine: a review, PC 9, 1988-9, 129-145.
202
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290. H. M. Alnuweiri and V. K. Prasanna-Kumar, An efficient VLSI architecture with applications to geometric problems, PC 12, 1989, 71-93. 291: T. Saito and H. Nishio, Structural and behavioral equivalence relations in automata networks, TCS 63, 1989, 223-237. 292. C. J. Zarowski, R. D. McLeod, and H. C. Card, Primitive cellular automata, threshold decomposition, and ranked order operations, T-CUMZ’ 38, 1989, 148-149. 293. R. S. Wallace and M. D. Howard, HBA vision architecture: built and benchmarked, T-PAMZ 11, 1989, 227-232. 294. H. Li and M. Maresca, Polymorphic-torus architecture for computer vision, T-PAMZ 11, 1989, 233-243. 295. W. Yang and A. M. Chiang, VLSI processor architectures for computer vision, IUW, 193-199. 296. J. A. Webb and M. B. MacPherson, The second DARPA Image Understanding Benchmark on Warp and extending Apply to include global operations, IUW, 597-616. 297. P. Kahn, D. Disabatino, and D. T. Lawton, MAC-II based IU environment development, IUW, 640-650. 298. K. Kim and V. K. Prasanna Kumar, Parallel memory systems for image processing, CVPR, 6.54-659. 299. D. Rhoden and C. Wilcox, Hardware acceleration for window systems, SIGGRAPH, 61-68. 300. M. Potmesil and E. M. Hoffert, The Pixel Machine: a parallel image computer, SIGGRAPH, 69-78. 301. H. Fuchs, J. Poulton, J. Eyles, T. Greer, J. Goldfeather, D. Ellsworth, S. Molnar, G. Turk, B. Tebbs, and L. Israel, Pixel-Planes 5: a heterogeneous multiprocessor graphics system using processor-enhanced memories, SIGGRAPH, 79-88.
0.4. Related Topics 302. T. L. Kunii, ed., Visual Database Systems (IFIP Working Conference, Tokyo, Japan, April 3-7, 19891, North-Holland, Amsterdam, 1989. 303. Symposium on the Design and Implementation of Large Spatial Databases, Santa Barbara, CA, July 17-18, 1989. 304. IEEE Workshop on Visual Languages, Rome, Italy, October 4-6, 1989. 305. E. A. Fox, guest ed., Special Section on Interactive Technology, Comm. ACM 32 (7), July 1989, 794-889. 306. W. I. Grosky and R. Mehrotra, guest eds., Image Database Management, Computer 22 (12), December 1989, 7-71. 307. G. C. Roman and K. C. Cox, A declarative approach to visualizing concurrent computations, Computer 22 (101, 1989, 25-36. 308. A. M. Goodman, R. M. Haralick, and L. G. Shapiro, Knowledge-based computer visionintegrated programming language and data management system design, Computer 22 (121, 1989, 43-54. 309. A. Pizano, A. Klinger, and A. Cardenas, Specification of spatial integrity constraints in pictorial database, Computer 22 (121, 1989, 59-71.
E. Computational Techniques E .1. Image Operations 310. J. Serra, guest ed., Special Issue on Advances in Mathematical Morphology, SP 16 (41, April 1989, 297-431. 311. K. S. Huang, Binary image algebra and optical cellular logic processor design, CVGZP 45, 1989, 295-345. 312. J. M. Rebordao, Lookup table loadings for image processing with controlled knots, CVGZP 47, 1989, 189-202. 313. G. E. Sotak, Jr. and K. L. Boyer, The Laplacian-of-Gaussian kernel: a formal analysis and design procedure for fast, accurate convolution and full-frame output, CVGZP 48, 1989, 147-189. 314. R. C. Staunton, The design of hexagonal sampling structures for image digitization and their use with local operators, TVC 7, 1989, 162-166. 315. P. J. Besl, J. B. Birch, and L. T. Watson, Robust window operators, MVA 2, 1989, 179-191.
IMAGE ANALYSIS AND COMPUTER
VISION:
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203
316. L. Ji, J. Piper, and J. Y. Tang, Erosion and dilation of binary images by arbitrary structuring elements using interval coding, PRL 9, 1989, 201-209. 317. A. Rosenfeld and J. M. Jolion, Local operations on labelled dot patterns, PRL 9, 1989, 225-232. 318. F. Meyer and J. Serra, Contrasts and activity lattice, S P 16, 1989, 303-317. 319. L. Vincent, Graphs and mathematical morphology, S P 16, 1989, 365-388. 320. M. Schmitt, Mathematical morphology and artificial intelligence: an automatic programming system, S P 16,1989,389-401. 321. J. P. F. D’Haeyer, Gaussian filtering of images: a regularization approach, S P 18, 1989, 169-181. 322. M. A. Sid-Ahmed, A systolic realization for 2-D digital filters, T-ASP 37, 1989, 560-565. 323. Z. Fang, X. Li, and L. M. Ni, On the communication complexity of generalized 2-D convolution on array processors, T-COMP 38, 1989, 184-194. 324. F. Y. C. Shih and 0. R. Mitchell, Threshold decomposition of gray-scale morphology into binary morphology, T-PAMI 11, 1989, 31-42. 325. P. Maragos, A representation theory for morphological image and signal processing, T-PAMI 11, 1989,586-599.
326. G. E. Sotak, Jr. and K. L. Boyer, Comments on “Fast convolution with Laplacian-of-Gaussian masks,” T-PAMZ 11, 1989, 1329-1332. 327. J. Xu, The optimal implementation of morphological operations on neighborhood connected array processors, CVPR, 166-171. 328. E. R. Dougherty, The dual representation of gray-scale morphological filters, CVPR, 172-177.
E.2. Multiresolution
and Scale Space Methods
329. S. L. Tanimoto, ed., Special Section on Multiresolution Representation, T-PAM1 11 (71, July 1989, 673-748. 330. P. Meer, Stochastic image pyramids, CVGIP 45, 1989, 269-294. 331. C. L. Tan and W. N. Martin, An analysis of a distributed multiresolution vision system, PR 22, 1989, 257-265. 332. N. G. Bourbakis and A. Klinger, A hierarchical picture coding scheme, PR 22. 1989, 317-329. 333. A. Toet, Image fusion by a ratio of low-pass pyramid, PRL. 9, 1989, 245-253. 334. A. Toet, A morphological pyramidal image decomposition, PRL 9, 1989, 255-261. 335. J. B. D. S. Martens and G. M. M. Majoor, The perceptual relevance of scale-space image coding, S P 17, 1989, 353-364.
336. B. Gidas, A renormalization group approach to image processing problems, T-PAM1 11, 1989, 164-180.
337. S. G. Mallat, A theory for multiresolution signal decomposition: the wavelet representation, T-PAMI 11, 1989, 674-693.
338. M. H. Chen and P. F. Yan, A multiscaling approach based on morphological filtering, T-PAM1 11, 1989, 694-700.
339. P. Maragos, Pattern spectrum and multiscale shape representation, T-PAMZ 11, 1989, 701-716. 340. S. Peleg, M. Werman, and H. Rom, A unified approach to the change of resolution: space and gray-level, T-PAM1 11, 1989, 739-742. 341. J. J. Koenderink, A hitherto unnoticed singularity of scale-space, T-PAMI 11, 1989, 1222-1224. 342. P. Meer, C. A. Sher, and A. Rosenfeld, Processing of line drawings in a hierarchical environment, CVPR, 638-645.
E.3. Geometric Transformations,
Calibration
343. D. Fraser, Comparison at high spatial frequencies of two-pass and one-pass geometric transformation algorithms, CVGZP 46, 1989, 267-283. 344. R. Horaud, B. Conio, 0. Leboulleux, and B. Lacolle, An analytic solution for the perspective 4-point problem, CVGIP 47, 1989, 33-44. 345. A. Goshtasby, Correction of image deformation from lens distortion using Bezier patches, CVGIP 47, 1989,385-394. 346. Z. Chen, D. C. Tseng, and J. Y. Lin, A simple vision algorithm for 3-D position determination using a single calibration object, PR 22, 1989, 173-187.
347. R. M. Haralick, Determining camera parameters from the perspective projection of a rectangle, PR 22,1989,223-230.
348. L. Lalitha and D. Dutta Majumder, Fractal based criteria to evaluate the performance of digital image magnification techniques, PRL. 9, 1989, 67-75.
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349. R. K. Lenz and R. Y. Tsai, Calibrating a Cartesian robot with eye-on-hand configuration independent of eye-to-hand relationship, T-PAMZ 11, 1989, 916-928. 350. E. L. Schwartz, A. Shaw, and E. Wolfson, A numerical solution to the generalized mapmaker’s problem: flattening nonconvex polyhedral surfaces, T-PAMZ 11, 1989, 1005-1008. 351. Y. C. Shiu and S. Ahmad, Calibration of wrist-mounted robotic sensors by solving homogeneous transform equations of the form Rx = XB, T-Z?,4 5, 1989, 16-29. 3.52. J. S. C. Yuan, A general photogrammetric method for determining object position and orientation, T-RA 5, 1989, 129-142. 353. R. Y. Tsai and R. K. Lenz, A new technique for fully autonomous and efficient 3D robotics hand/eye calibration, T-RA 5, 1989, 345-358. 354. G. Wolberg, Skeleton-based image warping, 1/% 5, 1989, 95-108. 355. Z. Zhuang and 0. D. Faugeras, Calibration of a mobile robot with application to visual navigation, WVM, 306-313. 356. R. Kumar, Determination of camera location and orientation, IUW, 870-881. 357. R. Horaud, B. Conio, 0. Leboulleux, and B. Lacolle, An analytic solution for the perspective 4-point problem, CVPR, 500-507. 358. J. K. Kearney, X. Yang, and S. Zhang, Camera calibration using geometric constraints, CVPR, 672-679. 359. M. Gangnet, J. C. Herve, T. Pudet, and J. M. Van Thong, Incremental computation of planar maps, SIGGRAPH, 345-354. 360. G. Wolberg and T. E. Boult, Separable image warping with spatial lookup tables, SIGGRAPH, 369-378. 361. R. Kumar and A. R. Hanson, Robust estimation of camera location and orientation from noisy data having outliers, WI3DS, 52-60. 362. Conference on Optical 3D Measurement Techniques, Vienna, Austria, September 18-20, 1989.
E.4. Interpolation, Function Fitting, etc. 363. R. Szeliski, &yes&r Modeling of Uncertainty in Low-Level Ksion, Kluwer, Boston, 1989. 364. E. Aarts and J. Korst, Simulated Annealing and Boltzmann Machines: A Stochastic Approach to Combinatorial Optimization and Neural Computing, Wiley, New York, 1989. 365. H. Imai, K. Kato, and P. Yamamoto, A linear-time algorithm for linear L, approximation of points, Algotithmica 4, 1989, 77-96. 366. A. L. Yuille, Energy functions for early vision and analog networks, BC 61, 1989, 115-123. 367. L. Piegl, A negative experiment with univariate blending functions, C& G 13, 1989, 217-222. 368. Y. Fletcher and D. F. McAllister, A tension-compatible patch for shape-preserving surface interpolation, CGA 9 (3), 1989, 45-55. 369. L. Piegl and W. Tiller, A menagerie of rational B-spline circles, CGA 9 (51, 1989, 48-56. 370. B. A. Barsky and T. DeRose, Geometric continuity of parametric curves: three equivalent characterizations, CGA 9 (61, 1989, 60-68. 371. N. Eichhorn and H. Kiesewetter, Integer analysis of two-dimensional polygonal objects, Computing 42, 1989, 1-16. 372. G. Walz, On interpolation by generalized planar splines I: The polynomial case, Computing 42, 1989, 187-194. 373. 0. Egecioglu, E. Gallopoulos, and C. K. Koc, Parallel Hermite interpolation: an algebraic approach, Computing 42, 1989, 291-307. 374. B. Pham, Conic B-splines for curve fitting: a unifying approach, CVGZP 45, 1989, 117-125. 375. M. Berman, Large sample bias in least squares estimators of a circular arc center and its radius, CVGZP 45, 1989, 126-128. 376. J. Y. Jou and A. C. Bovik, Improved initial approximation and intensity-guided discontinuity detection in visible-surface reconstruction, CVGZP 47, 1989, 292-326. 377. F. Cheng and A. Goshtasby, A parallel B-spline surface fitting algorithm, TOG 8, 1989, 41-50. 378. B. Joe, Multiple-knot and rational cubic Beta-splines, TOG 8, 1989, 100-120. 379. J. L. Mallet, Discrete smooth interpolation, TOG 8, 1989, 121-144. 380. J. Peters, Local generalized Hermite interpolation by quartic C2 space curves, TOG 8, 1989, 235-242. 381. H. Prautzsch, A round trip to B-splines via de Casteljau, TOG 8, 1989, 243-254. 382. X. Nie and R. Unbehauen, Efficient evaluation of 1-D and 2-D polynomials at equispaced points, T-ASSP 37, 1989, 1623-1626.
IMAGE ANALYSIS AND COMPUTER
VISION:
1989
205
383. A. Blake, Comparison of the efficiency of deterministic and stochastic algorithms for visual reconstruction, T-PAMI 11, 1989, 2-12. 385. C. H. Lee, Image surface approximation with irregular samples, T-PAM1 11. 1989, 206-212. 386. I. Weiss, Line fitting in a noisy image, T-PAM1 11, 1989, 325-329. 386. B. Shahraray and D. J. Anderson, Optimal estimation of contour properties by cross-validated regularization, T-PAMI 11, 1989, 600-610. 387. D. S. Chen, A data-driven intermediate level feature extraction algorithm, T-PAMI II, 1989. 749-758. 388. C. S. Fahn, J. F. Wang, and J. Y. Lee, An adaptive reduction procedure for the piecewise linear approximation of digitized curves, T-PAM1 11, 1989, 967-973. 389. B. Kamgar-Parsi, B. Kamgar-Parsi, and N. Netanyahu, A nonparametric method for fitting a straight line to a noisy image, T-PAMZ 11, 1989, 998-1001. 390. K. Harada and E. Nakamae, Sampling point setting on cubic splines for computer animation, VC 5, 1989, 14-21. 391. R. J. Low, Vector interpolation for surface normal calculation, VC 5, 1989, 158-159. 392. D. Geiger and F. Girosi, Mean field theory for surface reconstruction, IUW, 617-630. 393. D. Y. Kim. J. J. Kim, P. Meer, D. Mintz, and A. Rosenfeld, Robust computer vision: a least median of squares based approach, IUW, 1117-1134. 394. S. C. Liu and J. G. Harris, Generalized smoothing networks in early vision, CVPR, 184-191. 395. R. Szeliski, Fast surface interpolation using hierarchical basis functions, CVPR, 222-228. 396. S. S. Sinha and B. G. Schunck, Discontinuity preserving surface reconstruction, CVPR, 229-234. 397. C. L. Bajaj and I. Ihm, Hermite interpolation using real algebraic surfaces, CG, 94-103. 398. R. H. Bartels and R. T. Hardock, Curve-to-curve associations in spline-based inbetweening and sweeping, SIGGRAPH, 167-174. 399. R. L. Stevenson and E. J. Delp, Invariant reconstruction of visual surfaces, WDDS, 131-137. 400. J. L. Sanz, Multidimensional signal representation by zero crossings: an algebraic study, SIAM JC 49, 1989, 281-295. 401. K. M. Nashold and B. E. A. Saleh, Synthesis of two-dimensional binary images through band-limited systems: a slicing method, T-ASP 37, 1989, 1271-1279. 402. J. L. C. Sanz and T. T. Huang, Image representation by sign information, T-PAMI 11, 198’). 729-738.
F. Feature Detection, Segmentation, Image Ana&sis F.1. Feature Detection 403. N. K. Link and S. W. Zucker, Corner detection in curvilinear dot grouping. BC 59, 1988, 247-256. 404. L. J. van Vliet, I. T. Young, and G. L. Beckers, A nonlinear Laplace operator as edge detector in noisy images, CVGZP 45, 1989, 167-195. 405. B. Parvin and G. Medioni, Adaptive multiscale feature extraction from range data, CVGIP 45. 1989, 346-356. 406. L. J. Kitchen and J. A. Malin, The effect of spatial discretization on the magnitude and direction response of simple differential edge operators on a step edge, CVGIP 47, 1989, 243-258. 407. R. H. Park and W. Y. Choi, A new interpretation of the compass gradient edge operators. CVGIP 47, 1989, 259-265. 408. J. D. Cappelletti and A. Rosenfeld, Three-dimensional boundary following, CVGIP 48, 1989, 80-92. 409. K. Rangarajan, M. Shah, and D. Van Brackle, Optimal corner detector, CVGIP 48, 1989, 230-245. 410. P. L. Rosin and G. A. W. West, Segmentation of edges into lines and arcs, W C 7, 1989, 109-I 14. 411. J. M. Apffel, K. W. Current, J. L. C. Sanz, and A. K. Jain, An architecture for region boundary extraction in raster scan images suitable for VLSI implementation, M E A 2, 1989, 193-214. 412. M. H. Han, D. Jang, and J. Foster, Identification of cornerpoints of two-dimensional images using a line search method, PR 22, 1989, 13-20. 413. L. C. Topa and R. J. Schalkoff, Edge detection and thinning in time-varying image sequences using spatio-temporal templates, PR 22, 1989, 143-154. 414. P. Meer, S. Wang, and H. Wechsler, Edge detection by associative mapping, PR 22, 1989. 491-503.
206
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415. Y. S. Chen and W. H. Hsu, An interpretive model of line continuation in human visual perception, PR 22, 1989, 619-639. 416. J. Canning, J. J. Kim, N. Netanyahu, and A. Rosenfeld, Symbolic pixel labeling for curvilinear feature detection, PRL 8, 1988, 299-310. 417. A. Guiducci, Comer characterization by differential geometry techniques, PRL 8, 1988,311-318. 418. A. Premoli, P. Grattoni, and F. Pollastri, A non-sequential contour detection with a priori knowledge, PRL 9, 1989, 45-51. 419. R. Owens, S. Venkatesh, and J. Ross, Edge detection is a projection, PRL 9, 1989, 233-244. 420. B. B. Chaudhuri and B. U. Shankar, An efficient algorithm for extrema detection in digital images, PRL. 10, 1989,81-85. 421. M. Spann, C. Horne, and J. M. H. du Buf, The detection of thin structures in images, PRL. 10, 1989, 175-179.
422. M. Tanaka and T. Katayama, Edge detection and restoration of noisy images by the expectationmaximization algorithm, SP 17, 1989, 213-226. 423. J. J. Clark, Authenticating edges produced by zero-crossing algorithms, T-PAM1 11, 1989,43-57. 424. Y. T. Zhou, V. Venkateswar, and R. Chellappa, Edge detection and linear feature extraction using a 2-D random field model, T-PAMI 11, 1989, 84-95. 425. J. S. Chen, and G. Medioni, Detection, location, and estimation of edges, T-PAMI 11, 1989, 191-198. 426. Y. Lu and R. C. Jain, Behavior of edges in scale space, T-PAMI 11, 1989, 337-356. 427. P. Bouthemy, A maximum likelihood framework for determining moving edges, T-PAMZ 11, 1989,499-511.
428. P. Parent and S. W. Zucker, Trace inference, curvature consistency, and curve detection, T-PAMZ 11, 1989,823-839.
429. W. L. G. van Warmerdam and V. R. Algazi, Describing 1-D intensity transitions with Gaussian derivatives at the resolutions matching the transition widths, T-PAM1 11, 1989, 973-977. 430. E. De Micheli, B. Caprile, P. Ottonello, and V. Torre, Localization and noise in edge detection, T-PAMI 11, 1989, 1106-1117. 431. W. M. Krueger and K. Phillips, The geometry of differential operators with application to image processing, T-PAMZ 11, 1989, 1252-1264. 432. E. P. Lyvers, 0. R. Mitchell, M. L. Akey, and A. P. Reeves, Subpixel measurement using a moment-based edge operator, T-PAMZ 11, 1989, 1293-1309. 433. D. Lee, Edge detection, classification, and measurement, CVPR, 2-10. 434. A. Kundu, Robust edge detection, CVPR, 11-18. 435. J. S. Duncan and T. Birkholzer, Edge reinforcement using parameterized relaxation labeling, CVPR, 19-27. 436. 0. Monga and R. Deriche, 3D edge detection using recursive filtering: application to scanner images, CVPR, 28-35. 437. H. L. Tan, S. B. Gelfand, and E. J. Delp, A cost minimization approach to edge detection using simulated annealing, CVPR, 86-91. 438. A. M. M&or, Edge recognition in dynamic vision, CVPR, 118-123.
F.2. Segmentation 439. D. Blostein and N. Ahuja, A multiscale region detector, CVGIP 45, 1989, 22-41. 440. S. D. Yanowitz and A. M. Bruckstein, A new method for image segmentation, CVGIP 46, 1989, 82-95.
441. A. S. Abutaleb, Automatic thresholding of gray-level pictures using two-dimensional entropy, CVGIP 47, 1989, 22-32. 442. B. Kartikeyan and A. Sarkar, A unified approach for image segmentation using exact statistics, CVGZP 48, 1989, 217-229. 443. N. Ahuja and M. Tuceryan, Extraction of early perceptual structure in dot patterns: integrating region, boundary, and component Gestalt, CVGZP 48, 1989,304-356. 444. J. R. Beveridge, J. Griffith, R. R. Kohler, A. R. Hanson, and E. M. Riseman, Segmenting images using localized histograms and region merging, IJCV 2, 1989, 311-347. 445. Y. G. Leclerc, Constructing simple stable descriptions for image partitioning, ZJCV 3, 1989, 73-102. 446. D. H. Cooper, An object location strategy using shape and grey-level models, IVC 7, 1989, 50-56.
IMAGE ANALYSIS AND COMPUTER
VISION:
1989
207
447. B. J. Straub and W. E. Blanz, Combined decision theoretic and syntactic approach to image
segmentation, MVA 2, 1989, 17-30. 448. J. M. Jolion and A. Rosenfeld, Cluster detection in background noise, PR 22, 1989, 603-607. 449. S. Cho, R. Haralick, and S. Yi, Improvement of Kittler and Illingworth’s minimum error thresholding, PR 22, 1989, 609-617. 450. A. D. Brink, Grey-level thresholding of images using a correlation criterion, PRL. 9, 1989, 335-341. 451. J. M. Jolion and A. Rosenfeld, Coarse-fine bimodality analysis of circular histograms, PRL 10, 1989, 201-207. 452. N. R. Pal and S. K. Pal, Entropic thresholding, SP 16, 1989, 97-108. 453. J. M. Beaulieu and M. Goldberg, Hierarchy in picture segmentation: a stepwise optimization approach, T-PAMI 11, 1989, 150-163. 454. T. Bestul and L. S. Davis, On computing complete histograms of images in log(n) steps using hypercubes, T-PAM1 11, 1989, 212-213. 455. N. Yokoya and M. D. Levine, Range image segmentation based on differential geometry: a hybrid approach, T-PAM1 11, 1989, 643-649. 456. S. Lakshmanan and H. Derin, Simultaneous parameter estimation and segmentation of Gibbs random fields using simulated annealing, T-PAMI 11, 1989, 799-813. 457. Z. W. Bell, A Bayesian/Monte Carlo segmentation method for images dominated by Gaussian noise, T-PAM1 11, 1989, 985-990. 458. J. Goutsias and J. M. Mendel, Simultaneous optimal segmentation and model estimation of nonstationary noisy images, T-PAM1 11, 989, 990-998. 459. R. Mohan and R. Nevatia, Using perceptual organization to extract 3-D structures, T-PAMZ Il. 1989, 1121-1139. 460. J. S. Lee and M. C. K. Yang, Threshold selection using estimates from truncated normal distribution, T-SMC 19, 1989, 422-429. 461. A. K. C. Wong and P. K. Sahoo, A gray-level threshold selection method based on maximum entropy principle, T-SMC 19, 1989, 866-871. 462. E. Kawaguchi and R. I. Taniguchi, The depth first picture-expression as an image thresholding strategy, T-SMC 19, 1989, 1321-1328. 463. R. Mohan and R. Nevatia, Perceptual organization for segmentation and description, IIJW, 415-424. 464. P. Fua and A. J. Hanson, Objective functions for feature discrimination: theory, IUW, 443-460.
465. B. Bhanu, S. Lee, and J. Ming, Adaptive image segmentation using a genetic algorithm, IUW, 1043-1055. 466. Y. G. Leclerc, Image and boundary segmentation via minimal-length encoding on the Connection Machine, IUW, 1056-1069. 467. R. S. Wallace and T. Kanade, Finding hierarchical clusters by entropy minimization, IUW, 1105-1116. 468. J. Dolan and R. Weiss, Perceptual grouping of curved lines, IUW, 1135-1145. 469. E. Saund, Adding scale to the primal sketch, CVPR, 70-78. 470. L. H. Staib and J. S. Duncan, Parametrically deformable contour models, CVPR, 98-103. 471. R. Mohan and R. Nevatia, Segmentation and description based on perceptual organization, CVPR, 333-341. 472. A. Shio, An automatic thresholding algorithm based on an illumination-independent contrast measure, CVPR, 632-637. 473. P. Fua and A. J. Hanson, Objective functions for feature discrimination, IJCAI, 1596-1602. 474. E. P. D. Pednault, Some experiments in applying inductive inference principles to surface reconstruction, IJCAI, 1603-1609.
F.3. Image Analysis 475. J. Brolio, B. A. Draper, J. R. Beveridge, and A. R. Hanson, ISR: a database for symbolic processing in computer vision, Computer 22 (12), 1989, 22-30. 476. H. V. Jagadish and L. O’Gorman, An object model for image recognition, Computer 22 (12), 1989, 33-4 I. 477. N. Bartneck, A general data structure for image analysis, Computing 42, 1989. 17-34.
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478. T. Matsuyama, Expert systems for image processing: knowledge-based composition of image analysis processes, CI/GIP 48, 1989, 22-49. 479. B. A. Draper, R. T. Collins, J. Brolio, A. R. Hanson, and E. M. Riseman, The schema system, IJCV 2, 1989, 209-250. 480. V. V. Alexandrov and N. D. Gorsky, Expert systems simulating human visual perception, ZJPRAZ 3, 1989, 19-28. 481. S. N. Srihari and Z. Xiang, Spatial knowledge representation, ZJPRAZ 3, 1989, 67-84. 482. P. W. Woods, D. Pycock, and C. J. Taylor, A frame-based system for modelling and executing visual tasks, NC 7, 1989, 102-108. 483. S. Hopkins. G. J. Michaelson, and A. M. Wallace, Parallel imperative and functional approaches to visual scene labelling, ZPC 7, 1989, 178-193. 484. A. M. Wallace and P. McAndrew, Inferring the presence of objects from feature data, PRL 9, 1989, 287-295. 485. P. Bottom, P. Mussio, M. Protti, and R. Schettini, Knowledge-based contextual recognition and seiving of digital images, PRL 10, 1989, 101-110. 486. A. F. Bobick and R. C. Bolles, Representation space: an approach to the integration of visual information, II-W, 263-272. 487. T. S. Levitt, T. 0. Binford, G. J. Ettinger, and P. Gelband, Probability-based control for computer vision, IUW, 355-369. 488. W. Harvey, D. Kalp, M. Tambe, D. McKeown, and A. Newell, Measuring the effectiveness of task-level parallelism for high-level vision, II-W, 916-933. 489. S. Edelman and T. Poggio, Representations in high-level vision: reassessing the inverse optics paradigm, IUW, 944-949. 490. J. W. Modestino and J. Zhang, A Markov random field model-based approach to image interpretation, CVPR, 458-465. 491. A. F. Bobick and R. Bolles, Representation space: an approach to the integration of visual information, CVPR, 492-499. 492. J. Segen, Model learning and recognition of nonrigid objects, CVPR, 597-602. 493. V. Honavar and L. Uhr, Generation, local receptive fields and global convergence improve perceptual learning in connectionist networks, IJCAI, 180-185. 494. D. Kapur and J. Mundy, eds., Special Volume on Geometric Reasoning, AZ 37 (l-3), December 1988, 1-412. 495. D. Kapur and J. Mundy, eds., Geomehic Reasoning, MIT Press, Cambridge, MA, 1989. 496. D. Kapur and J. L. Mundy, Geometric reasoning and artificial intelligence: introduction to the special volume, AZ 37, 1988, l-11. 497. D. Kapur and J. L. Mundy, Wu’s method and its application to perspective viewing, AZ 37, 1988, 15-36. 498. D. S. Arnon, Geometric reasoning with logic and algebra, AZ 37, 1988, 37-60. 499. D. Kapur, A refutational approach to geometry theorem proving, AZ 37, 1988, 61-93. 500. H. P. Ko, Geometry theorem proving by decomposition of quasi-algebraic sets: an application of the Ritt-Wu principle, AZ 37, 1988, 95-122. 501. J. A. Goguen, Modular algebraic specification of some basic geometrical constructions, AZ 37, 1988, 123-153. 502. S. C. Chou and J. G. Yang, On the algebraic formulation of certain geometry statements and mechanical geometry theorem proving, Algorirhmica 4, 1989, 237-262. 503. D. Wang, On Wu’s method for proving constructive geometric theorems, IJCAI, 419-424. 504. M. Y. Kim, Visual reasoning in geometry theorem proving, IJCAI, 1617-1622. 505. R. B. Fisher and M. J. L. Orr, Experiments with a network-based geometric reasoning engine, IJCAI, 1623-1627. 506. M. Flasinski, Characteristics of edNLC-graph grammar for syntactic pattern recognition, CVGZP 47, 1989, 1-21. 507. A. Szepietowski, On three-way two-dimensional Turing machines, IS 47, 1989, 135-147. 508. J. Hromkovic, K. Inoue, and I. Takanami, Lower bounds for language recognition on two-dimensional alternating multihead machines, JCSS 38, 1989, 431-451. 509. A. Ito, K. Inoue, and I. Takanami, Deterministic two-dimensional on-line tessellation acceptors are equivalent to two-way two-dimensional alternating finite automata through 180 degree rotation, TCS 66, 1989, 273-287.
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209
510. U. Huckenbeck, Euclidean geometry in terms of automata theory, TCS 68, 1989, 71-87. 511. J. Clayson, Visual Modeling with LOGO-A Structured Approach to Seeing, MIT Press, Cambridge, MA, 1988. 512. H. Cohen, How to draw three people in a botanical garden, AAAI, 846-855.
G. Matching, G.l.
Stereo, and Time-Varying Imagery
Matching
513. C. Zetzsche and T. Caelli, Invariant pattern recognition using multiple filter image representations, CVGZP 45, 1989, 251-262. 514. R. Bajcsy and S. Kovacic, Multiresolution elastic matching, CVGIP 46, 1989, 1-21. 515. M. Herbin, A. Venot, J. Y. Devaux, E. Walter, J. F. Lebruchec, L. Dubertret, and J. C. Roucayrol, Automated registration of dissimilar images: application to medical imagery, CVGZP 47, 1989,77-88. 516. E. E. Milios, Shape matching using curvature processes, CVGIP 47, 1989, 203-226. 517. W. E. L. Grimson, On the recognition of parameterized 2D objects, IJCV 3, 1989, 353-372.
518. B. Yang, W. E. Snyder, and G. L. Bilbro, Matching oversegmented 3D images to models using association graphs, IVC 7, 1989, 135-143. 519. A. A. Amini, T. E. Weymouth, and D. J. Anderson, A parallel algorithm for determining two-dimensional object positions using incomplete information about their boundaries, PR 22, 1989, 21-28. 520. R. Sitaraman and A. Rosenfeld, Probabilistic analysis of two stage matching, PR 22, 1989, 331-343. 521. J. D. Tubbs, A note on binary template matching, PR 22, 1989, 359-365.
522. W. Wang, S. S. lyengar, and L. M. Patnaik, Memory-based reasoning approach for pattern recognition of binary images, PR 22, 1989,505-518. 523. Z. Jiang and W. Lu, A new digital image registration algorithm based on the double spatial intensity gradients using pyramids, PRL 8, 1988, 335-340. 524. T. G. Ryall and J. Sandor, Statistical pattern matching, PRL 9, 1989, 163-168. 525. P. Cox, H. Maitre, M. Minoux, and C. Ribeiro, Optimal matching of convex polygons, PRL 9, 1989,327-334. 526. H. Maitre and Y. Wu, A dynamic programming algorithm for elastic registration of distorted pictures based on autoregressive models, T-ASSP 37, 1989, 288-297. 527. S. S. Venkatesh and D. Psaltis, Binary filters for pattern classification, T-ASSP 37, 1989,604-611. 528. W. E. L. Grimson, On the recognition of curved objects, T-PAMI 11, 1989, 632-643.
529. V. K. Prasanna Kumar and V. Krishnan, Efficient parallel algorithms for image template matching on hypercube SIMD machines, T-PAM 11, 1989, 665-669. 530. R. Mehrotra and W. I. Grosky, Shape matching utilizing indexed hypothesis generation and testing, T-RA 5, 1989, 70-77. 531. T. C. Pong and B. G. Kaiser, A hierarchical approach to the correspondence problem, T-SMC 19,1989,271-276. 532. R. C. Nelson, Visual homing using an associative memory, IUW, 245-262.
533. F. P. Perlant and D. M. McKeown, Scene registration in aerial image analysis, IUW, 309-331. 534. J. R. Beveridge, R. Weiss, and E. M. Riseman, Optimization of 2-dimensional model matching, IUW, 815-830. 535. B. Kamgar-Parsi, J. L. Jones, and A. Rosenfeld, Registration of multiple overlapping range images: scenes without distinctive features, CVPR, 282-290. 536. D. B. Gennery, Visual terrain matching for a Mars rover, CVPR, 483-491. 537. J. K. Tsotsos, The complexity of perceptual search tasks, IJCAI, 1571-1577. 538. T. Risse, Hough transform for line recognition: complexity of evidence accumulation and cluster detection, CVGIP 46, 1989, 327-345. 539. H. K. Yuen, J. lllingworth, and J. Kittler, Detecting partially occluded ellipses using the Hough transform, n/C 7, 1989, 31-37. 540. D. Ben-Tzvi, A. A. Naqvi, and M. Sandler, Efficient parallel implementation of the Hough transform on a distributed memory system, NC 7, 1989, 167-172. 541. C. Guerra and S. Hambrusch, Parallel algorithms for line detection on a mesh, JPDC 6, 1989. l-19.
210
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542. E. R. Davies, Finding ellipses using the generalised Hough transform, PRL 9, 1989, 87-96. 543. E. R. Davies, Minimising the search space for polygon detection using the generalised Hough transform, PRL 9, 1989, 181-192. 544. J. M. Jolion and A. Rosenfeld, An O(log nl pyramid Hough transform, PRL 9, 1989, 343-349. 545. C. L. Huang, Elliptical feature extraction via an improved Hough transform, PRL 10, 1989, 93-100. 546. E. R. Davies, Occlusion analysis for object detection using the generalised Hough transform, SP 16, 1989, 267-277. 547. A. L. Fisher and P. T. Highnam, Computing the Hough transform on a scan line array processor, T-PAMI 11, 1989, 262-265. 548. I. D. Svalbe, Natural representations for straight lines and the Hough transform on discrete arrays, T-PAM1 11, 1989, 941-950. 549. A. Califano, Feature recognition using correlated information contained in multiple neighborhoods, AAAI, 831-836. 550. J. Princen, J. Illingworth, and J. Kittler, A hierarchical approach to line extraction, CVPR, 92-97. 551. A. Califano, R. M. Belle, and R. W. Taylor, Generalized neighborhoods: a new approach to complex parameter feature extraction, CVPR, 192-199. 552. P. M. Vaidya, Approximate minimum weight matching on points in k-dimensional space, Algotithmica 4, 1989, 569-583. 553. R. F. Zhu and T. Takaoka, A technique for two-dimensional pattern matching, Comm. ACM 32, 1989, 1110-1120. 554. J. S. Turner, Approximation algorithms for the shortest common superstring problem, IC 83, 1989, l-20. 555. C. Consel and 0. Danvy, Partial evaluation of pattern matching in strings, IPL 30, 1989, 79-86. 556. E. Makinen, On the subtree isomorphism problem for ordered trees, IPL 32, 1989, 271-273. 557. G. M. Landau and U. Vishkin, Fast parallel and serial approximate string matching, J. A1gotithm.s 10, 1989, 157-169. 558. P. M. Griffin, Correspondence of 2-D projections by bipartite matching, PRL 9, 1989, 361-366. 559. P. M. Vaidya, Geometry helps in matching, SZAMJC 18, 1989, 1201-1225. 560. K. Zhang and D. Shasha, Simple fast algorithms for the editing distance between trees and related problems, SOlMJC 18, 1989, 1245-1261. 561. T. Eilam-Tzoreff and U. Vishkin, Matching patterns in strings subject to multi-linear transformations, TCS 60, 1988, 231-254. 562. A. Mukherjee, Hardware algorithms for determining similarity between two strings, T-COMP 38, 1989, 600-603. 563. A. M. Landraud, J. F. Avril, and P. Chretienne, An algorithm for finding a common structure shared by a family of strings, T-PAMZ 11, 1989, 890-895. 564. P. M. Griffin and C. Alexopoulos, Point pattern matching using centroid bounding, T-SK 19, 1989, 1274-1276. 565. K. Imai, S. Sumino, and H. Imai, Minimax geometric fitting of two corresponding sets of points, CG, 266-275. 566. 0. Marcotte and S. Suri, On geometric matching, CG, 302-314.
G.2. Stereo 567. S. T. Barnard, Stochastic stereo matching over scale, ZJCV 3, 1989, 17-32. 568. G. P. Otto and T. K. W. Chau, “Region-growing” algorithm for matching of terrain images, IVC 7, 1989, 83-94. 569. T. Day and J. P. Muller, Digital elevation model production by stereo-matching SPOT image pairs: a comparison of two algorithms, NC 7, 1989, 95-101. 570. Z. D. Hua and B. Dubuisson, String matching for stereo vision, PRL 9, 1989, 117-126. 571. T. C. Pong, R. M. Haralick, and L. G. Shapiro, Matching topographic structures in stereo vision, PRL 9, 1989, 127-136. 572. F. E. E. Omoruto and J. P. Raina, Concise vector equations for stereopsis, PRL 9, 1989, 367-372. 573. R. March, A regularization model for stereo vision with controlled continuity, PRL 10, 1989, 259-263.
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211
574. R. Mohan, G. Medioni, and R. Nevatia, Stereo error detection, correction, and evaluation, T-F’Ah4I 11, 1989, 113-120. 575. W. Hoff and N. Ahuja, Surfaces from stereo: integrating feature matching, disparity estimation. and contour detection, T-PAMI 11, 1989, 121-136. 576. Y. Yeshurun and E. L. Schwartz, Cepstral filtering on a columnar image architecture: a fast algorithm for binocular stereo segmentation, T-PAMI 11, 1989, 759-767. 577. Y. C. Shah, R. Chapman, and R. B. Mahani, A new technique to extract range information from stereo images, T-PAMZ 11, 1989, 768-773. 578. N. AIvertos, D. Brzakovic, and R. C. Gonzalez, Camera geometries for image matching in 3-D machine vision, T-PAMZ 11, 1989, 897-915. 579. R. Horaud and T. Skordas, Stereo correspondence through feature grouping and maximal cliques, T-PAMI 11, 1989, 1168-1180. 580. D. Weinshall, Qualitative shape from stereo, IUW, 850-856. 581. S. D. Cochran and G. Medioni, Accurate surface description from binocular stereo, IIJW. 857-869. 582. S. T. Barnard, Stochastic stereo matching on the Connection Machine, IUW, 1021-1031.
583. A. D. Jepson and M. R. M. Jenkin, The fast computation of disparity from phase differences. CVPR, 398-403.
584. T. J. Olson and R. D. Potter, Real-time vergence control, CVPR, 404-409. 585. L. B. Wolff, Accurate measurement of orientation from stereo using line correspondence, CVPR, 410-415. 586. L. Cohen, L. Vinet, P. T. Sander, and A. Gagalowicz, Hierarchical region based stereo matching. CVPR, 416-421. 597. T. Morita, Y. Yasukawa, Y. Inamoto, T. Uchiyama, and S. Kawakami, Measurement in three dimensions by motion stereo and spherical mapping, CVPR, 422-428. 588. A. E. Kayaalp, A. R. Rao, and R. Jain, Scanning electron microscope based stereo analysis. CVPR, 429-434.
589. J. R. Jordan III, A. C. Bovik, and W. S. Geisler, Chromatic stereopsis, IJCAI, 164991654. 590. L. B. Wolff and T. E. Boult, Using line correspondence stereo to measure surface orientation, IJCAI, 1655-1660. 591. G. Xu, H. Kondo, and S. Tsuji, A region-based stereo algorithm, IJCAI, 1661-1666. 592. R. P. Wildes, An analysis of stereo disparity for the recovery of three-dimensional scene geometry, WI3DS, 2-8. 593. S. Das and N. Ahuja, Integrating multiresolution image acquisition and coarse-to-fine surface reconstruction from stereo, WI3DS, 9-15. 594. S. D. Cochran and G. Medioni, Accurate surface description from binocular stereo, WI3DS. 16-23. 595. R. Vaillant and 0. D. Faugeras, Using occluding contours for recovering shape properties of
objects, WI3DS, 26-32.
G.3. Motion 596. Proceedings, Workshop on Visual Motion, Irvine, CA, March 20-22, 1989. 597. W. B. Thompson, guest ed., Special Issue on Visual Motion, T-PAMZ 11 (5), May 1989, 449-541. 598. S. Uras, F. Girosi, A. Verri, and V. Torre, A computational approach to motion perception, BC 60, 1988, 79-87. 599. J. AIoimonos and C. M. Brown, On the kinetic depth effect, BC 60, 1989, 445-455.
600. N. Kehtarnavaz and S. Mohan, A framework for estimation of motion parameters from range images, CVGIP 45, 1989, 88-105. 601. S. P. Liou and R. C. Jain, Motion detection in spatio-temporal space, CVGIP 45, 1989, 227-250. 602. X. Zhuang, A simplification to linear two-view motion algorithms, CVGZP 46, 1989, 175-178. 603. S. Negahdaripour and B. K. P. Horn, A direct method for locating the focus of expansion, CVGIP 46, 1989, 303-326. 604. K. Skifstad and R. Jain, Illumination sequences, CVGIP 46, 1989, 387-399.
independent change detection for real world image
605. A. Mitiche, 0. Faugeras, and J. K. Aggarwal, Counting straight lines, CVGIP 47, 1989, 353-360. 606. P. Anandan, A computational framework and an algorithm, for the measurement of structure from motion, IJCV 2, 1989, 283-310.
212
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607. J. J. Wu, R. E. Rink, T. M. Caelli, and V. G. Gourishankar, Recovery of the 3-D location and motion of a rigid object through camera image (an extended Kalman filter approach), ZJCV 2, 1989,373-394. 608. F. Bergholm, Motion from flow along contours: a note on robustness and ambiguous cases, ZZCV 2, 1989, 395-415. 609. H. H. Baker and R. C. Bolles, Generalizing epipolar-plane image analysis on the spatiotemporal surface, ZZCV 3, 1989, 33-49. 610. H. H. Baker, Building surfaces of evolution: the weaving wall, ZZCV 3, 1989, 51-71. 611. A. L. Yuille and N. M. Grzywacz, A mathematical analysis of the motion coherence theory, ZJCV 3, 1989, 155-175. 612. D. W. Murray, D. A. Castelow, and B. F. Buxton, From image sequences to recognized moving polyhedral objects, ZJCV 3, 1989, 181-208. 613. L. Matthies, T. Kanade, and R. Szeliski, Kalman filter-based algorithms for estimating depth from image sequences, ZJCV 3, 1989, 209-236. 614. S. Negahdaripour, Critical surface pairs and triplets, ZJCV 3, 1989, 293-312. 615. D. Charnley and R. Blissett, Surface reconstruction from outdoor image sequences, ZVC 7, 1989, 10-16. 616. M. Stephens and C. Harris, 3D wire-frame integration from image sequences, II/C 7, 1989, 24-30. 617. K. J. Hanna and L. Tarassenko, Tracking cataract by the “four-line” method, IVC 7, 1989, 57-62. 618. I. Hadani and E. Barta, The hybrid constraint equation for motion extraction, NC 7, 1989, 217-224. 619. T. J. Broida and R. Chellappa, Performance bounds for estimating three-dimensional motion parameters from a sequence of noisy images, JO&l A6, 1989, 879-889. 620. R. Jasinschi and A. Yuille, Nonrigid motion and Regge calculus, JOSA A6, 1989, 1088-1095. 621. K. Skifstad and R. Jain, Range estimation from intensity gradient analysis, WA 2, 1989,81-102. 622. V. S. S. Hwang, Tracking feature points in time-varying images using an opportunistic selection approach, PR 22, 1989, 247-256. 623. A. Mitiche and G. Habelrih, Interpretation of straight line correspondences using angular relations, PR 22, 1989, 299-308. 624. C. M. Jong and E. Salari, Analysis of image deformation under orthographic projection and flow parameter estimation, PR 22, 1989, 309-315. 625. T. L. Huntsberger and S. N. Jayaramamurthy, Determination of the optic flow field in the presence of occlusion, PZU 8, 1988, 325-333. 626. S. H. Lai and S. Chang, Estimation of 3-D translational motion parameters via Hadamard transform, PRL 8, 1988, 341-345. 627. I. Dinstein, A new technique for visual motion alarm, PRL 8, 1988, 347-351. 628. J. Arnspang, On the use of the horizon of a translating planar curve, PRL 10, 1989, 61-69. 629. J. Arnspang and J. Ma, Image irradiance equations for a zooming camera, PZU 10, 1989, 189-194. 630. C. W. Fu and S. Chang, A motion estimation algorithm under time-varying illumination, PZU 10, 1989, 195-199. 631. D. D. Giusto and G. Vemazza, Optical flow calculation from feature space analysis through an automatic segmentation process, SP 16, 1989, 41-51. 632. G. Tziritas, Recursive and/or iterative estimation of the two-dimensional velocity field and reconstruction of three-dimensional motion, SP 16, 1989, 53-72. 633. T. Reuter, Standards conversion using motion compensation, SP 16, 1989, 73-82. 634. M. Hoetter, Differential estimation of the global motion parameters zoom and pan, SP 16, 1989, 249-265. 635. A. Mecocci, Moving object recognition and classification in external environments, SP 18, 1989, 183-194. 636. W. Y. Choi and R. H. Park, Motion vector coding with conditional transmission, SP 18, 1989, 259-267. 637. T. J. Patterson, D. M. Chabries, and R. W. Christiansen, Detection algorithms for image sequence analysis, T-ASSP 37, 1989, 1454-1458.
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213
638. H. H. Nagel, On a constraint equation for the estimation of displacement rates in image sequences, T-PAMI 11, 1989, 13-30. 639. M. Subbarao, Interpretation of image flow: a spatio-temporal approach, T-PAM1 11, 1989, 266-278. 640. D. J. Fleet and A. D. Jepson, Hierarchical filters, T-PAMZ 11, 1989, 315-325.
construction of orientation and velocity sensitive
641. J. Weng, T. S. Huang, and N. Ahuja, Motion and structure from two perspective views: algorithms, error analysis, and error estimation, T-PAMZ 11, 1989, 451-476. 642. G. Adiv, Inherent ambiguities in recovering 3-D motion and structure from a noisy flow field. T-PAMZ 11, 1989,477-480.
643. A. Verri and T. Poggio, Motion field and optical flow: qualitative properties, T-PAMZ 11, 1989. 490-498. 644. J. Aisbett,
Optical flow with an intensity-weighted smoothing, T-PAMZ 11, 1989, 512-522. 645. M. A. Snyder, The precision of 3-D parameters in correspondence-based techniques: the case of uniform translational motion in a rigid environment, T-PAMZ 11, 1989, 523-528. 646. M. Yamamoto, A general aperture problem for direct estimation of 3-D motion parameters. T-PAMZ 11, 1989, 528-536.
647. T. S. Huang and C. H. Lee, Motion and structure from orthographic projections, T-PAMZ 11, 1989, 536-540. 648. A. Mitiche, A comment on “On kineopsis and computation of structure and motion.” T-PAM1 11, 1989, 540-541.
649. P. Strobach, Quadtree-structured
linear prediction models for image sequence processing,
T-PAMZ 11, 1989, 742-748.
650. B. G. Schunck, Image flow segmentation and estimation by constraint line clustering, T-PAMZ 11, 1989, 1010-1027. 651. R. C. Nelson and J. (Y.) Aloimonos, Obstacle avoidance using flow field divergence, T-PAM1 11. 1989, 1102-1106. 652 T. S. Huang and 0. D. Fagueras, Some properties of the E matrix in two-view motion estimation, T-PAMZ 11, 1989, 1310-1312. 653. W. M. Wells III, Visual estimation of 3-D line segments from motion--a mobile robot vision system, T-R4 5, 1989, 820-825. 654. J. J. Leou and W. H. Tsai, New sensing strategies for monitoring moving polyhedral objects by machine vision, T-SMC 19, 1989, 872-880. 655. I. D. Horswill and R. A. Brooks, Situated vision in a dynamic world: chasing objects, AAAI. 796-800. 656. P. J. Burt, J. R. Bergen, R. Hingorani, R. Kolczynski, W. A. Lee, A. Leung, J. Lubin, and H.
Shvaytser, Object tracking with a moving camera, WVM, 2-12. 657. G. L. Gordon, On the tracking of featureless objects with occlusion, WVM, 13-20. 658. T. J. Broida and R. Chellappa, Experiments and uniqueness results on object structure and kinematics from a sequence of monocular images, WVM, 21-30. 659. M. R. M. Jenkin and A. D. Jepson, Measuring trajectory, WVM, 31-37. 660. J. P. Gambotta, Tracking points and line segments in image sequences, WVM, 38-45. 661. C. N. Lee, R. M. Haralick, and X. Zhuang, Recovering 3-D motion parameters from image sequences with gross errors, WVM, 46-53. 662. J. Arnspang, Moving towards the horizon of a planar curve, WVM, 54-59. 663. C. Koch, H. T. Wang, B. Mathur, A. Hsu, and H. Suarez, Computing optical flow in resistive networks and in the primate visual system, WVM, 62-72. 664. S. Gong, Curve motion constraint equation and its applications, WVM, 73-80. 665. D. Shulman and J. Y. He&, Regularization of discontinuous flow fields, WVM, 81-86. 666. S. V. Fogel, Implementation of a nonlinear approach to the motion correspondence problem, WVM, 87-98. 667. D. Lee, A. Papageorgiou, and G. W. Wasilkowski, Computing optical flow, WVM, 99-106. 668. M. A. Snyder, On the mathematical foundations of smoothness constraints for the determination of optical flow and for surface reconstruction, WVM, 107-115. 669. F. Girosi, A. Verri, and V. Torre, Constraints for the computation of optical flow. WVM. 116-124.
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AZRIEL
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670. J. J. Little and A. Verri, Analysis of differential and matching methods for optical flow, WVM, 173-180. 671. J. A. Perrone, In search of the elusive flow field, WVM, 181-188. 672. A. Verri, F. Girosi, and V. Torre, Mathematical properties of the 2D motion field: from singular points to motion parameters, WVM, 190-200. 673. W. B. Thompson, Structure-from-motion by tracking occlusion boundaries, WVM, 201-203. 674. R. Laganiere and A. Mitiche, On combining points and lines in an image sequence to recover 3D structure and motion, WVM, 221-228. 675. M. E. Spetsakis and J. (Y.1 Aloimonos, Optimal motion estimation, WVM, 229-237. 676. B. M. Bennett, D. D. Hoffman, J. E. Nicola, and C. Prakash, Inferring structure from motion: a homotopy algorithm, WVM, 238-245. 677. 0. D. Faugeras and S. Maybank, Motion from point matches: multiplicity of solutions, WVM, 248-255. 678. R. A. Jaenicke, Structure from limited motion of complex rigid objects, WVM, 256-263. 679. R. Manmatha, R. Dutta, E. M. Riseman, and M. A. Snyder, Issues in extracting motion parameters and depth from approximate translational motion, WVM, 264-272. 680. S. L. Iu and K. Wohn, Estimation of 3-D motion and structure based on a temporally-oriented approach with the method of regression, WVM, 273-281. 681. W. 0. Franzen, Representing motion through chronogeneous transformations, WVM, 282-289. 682. H. H. Chen and T. S. Huang, Using motion from orthographic projections to prove 3-D point matches, WVM, 290-297. 683. E. D. Dickmanns, Subject-object discrimination in 4D-dynamic scene interpretation of machine vision, WVM, 298-304. 684. T. C. Pong, M. A. Kenner, and J. Otis, Stereo/motion cues in preattentive vision processing: some experiments with random-dot stereographic image sequences, WVM, 314-320. 685. M. K. Leung, A. N. Choudhaty, J. H. Patel, and T. S. Huang, Point matching in a time sequence of stereo image pairs and its parallel implementation on a multiprocessor, WVM, 321-328. 686. L. Li and J. H. Duncan, Recovering 3-D translational motion and establishing stereo correspondence from binocular image flows, WVM, 329-336. 687. R. Samadani, Changes in connectivity in active contour models, WVM, 337-343. 688. S. L. Peng and G. Medioni, Interpretation of image sequences by spatio-temporal analysis, WVM, 344-351. 689. D. B. Goldgof, T. S. Huang, and H. Lee, Motion estimation from points without correspondences from orthographic projections, WVM, 352-358. 690. J. Weng, T. S. Huang, and N. Ahuja, Motion from images: image matching, parameter estimation and intrinsic stability, WVM, 359-366. 691. B. Bhanu, P. Symosek, J. Ming, W. Burger, H. Nasr, and J. Kim, Qualitative target motion detection and tracking, IUW, 370-398. 692. L. S. Davis, D. DeMenthon, T. Bestul, D. Harwood, H. V. Srinivasan, and S. Ziavras, RAMBO -vision and planning on the Connection Machine, IUW, 631-639. 693. C. Brown, H. Durrant-Whyte, J. Leonard, and B. Rao, Centralized and decentralized Kalman filter techniques for tracking, navigation, and control, IUW, 651-675. 694. P. K. Allen, Real-time motion tracking using spatio-temporal filters, IUW, 695-701. 695. J. Heel, Dynamic motion vision, IUW, 702-713. 696. R. Dutta, R. Manmatha, L. R. Williams, and E. M. Riseman, A data set for quantitative motion analysis, IUW, 714-720. 697. B. Bhanu, B. Roberts, and J. Ming, Inertial navigation sensor integrated motion analysis, IUW, 747-763. 698 S. L. Gazit and G. Medioni, Multi-scale contour matching in a motion sequence, IUW, 934-943. 699. A. Singh, Image-flow estimation: an information fusion approach, IUW, 983-991. 700. H. S. Sawhney and J. Oliensis, Description and interpretation of rotational motion from image trajectories, IUW, 992-1003. 701. M. A. Snyder, On the mathematical foundations of smoothness constraints for the determination of optical flow and for surface reconstruction, IUW, 1004-1011. 702. P. Balasubramanyam and R. Weiss, Early identification of occlusion in stereo-motion image sequences, IUW, 1032-1037.
IMAGE ANALYSIS AND COMPUTER
VISION:
1989
215
703. K. Gould and M. Shah, The trajectory primal sketch: a multi-scale scheme for representing motion characteristics, CVPR, 79-85. 704. J. Wu, R. Brockett, and K. Wohn, A contour-based recovery of image flow: iterative method, CVPR, 124-129. 705. C. S. Fuh and P. Maragos, Region-based optical flow estimation, CVPR, 130-135. 706. R. V. Raja Kumar, A. Tirumalai, and R. C. Jain, A non-linear optimization algorithm for the estimation of structure and motion parameters, CVPR, 136-143. 707. J. Weng, N. Ahuja, and T. S. Huang, Optimal motion and structure estimation, CVPR, 144-152. 708. J. F. Bronskill, J. S. A. Hepburn, and W. K. Au, A knowledge-based approach to the detection, tracking and classification of target formations in infrared image sequences, CVPR, 153-158. 709. R. Dutta, R. Manmatha, L. R. Williams, and E. M. Riseman, A data set for quantitative motion analysis, CVPR, 159-164. 710. F. Jiang and T. E. Weymouth, Depth from dynamic stereo images, CVPR, 250-255. 711. S. Chaudhuri and S. Chatterjee, Estimation of motion parameters for a deformable object from range data, CVPR, 291-295. 712. D. J. Fleet and A. D. Jepson, Computation of normal velocity from local phase information, CVPR, 379-386. 713. M. J. Stephens, R. J. Blissett, D. Charnley, E. P. Sparks, and J. M. Pike, Outdoor vehicle navigation using passive 3D vision, CVPR, 556-562. 714. W. Burger and B. Bhanu, On computing a “fuzzy” focus of expansion for autonomous navigation, CVPR, 563-568. 715. Y. F. Wang and A. Pandey, Interpretation of 3D structure and motion using structured lighting, WI3DS, 84-90. 716. M. Xie and P. Rives, Towards dynamic vision, WI3DS, 91-99. 717. C. Brown, Kinematic and 3D motion prediction for gaze control, WI3DS, 145-151. 718. The Visual Processing of Motion (C.N.R.S. Jacques Monod Conference), Roscoff, France, June 19-23, 1989. 719. C. Chubb and G. Sperling, Second-order motion perception: space/time separable mechanisms, WVM, 126-138. 720. R. S. Jasinschi, Towards a theory of apparent visual motion, WVM, 139-147. 721. N. M. Grzywacz, J. A. Smith, and A. L. Yuille, A common theoretical framework for visual motion’s spatial and temporal coherence, WVM, 148-155. 722. A. M. Waxman, J. Wu, and M. Seibert, Computing visual motion in the short and the long: from receptive fields to neural networks, WVM, 156-164. 723. H. H. Biilthoff, J. J. Little, and T. Poggio, A parallel motion algorithm consistent with psychophysics and physiology, WVM, 165-172. 724. J. M. Loomis and D. W. Eby, Relative motion parallax and the perception of structure from motion, WVM, 204-211. 725. N. H. Goddard, The interpretation of visual motion: recognizing moving light displays, WVM, 212-220. 726. (L. Liu), (N. Zhao), and (Z. Bian), Can early stage vision detect topology, IJCAI, 1591-1595.
H. Shape and Pattern H.1. Representations, Topology, etc. 727. H. Samet, The Design and Analysis of Spatial Data Shuctures, Addison-Wesley, Reading, MA, 1990. 728. H. Samet, Applications of Spatial Data Structures, Addison-Wesley, Reading, MA, 1990. 729. P. Gao and T. R. Smith, Space efficient hierarchical structures: relatively addressed compact quadtrees for GISs, ZVC 7, 1989, 173-177. 730. H. Kiem and P. N. Khoi, Space efficiency analysis of some methods of image representation, J. New Generation Computing Systems 1, 1988, 353-359.
731. Y. Hung and A. Rosenfeld, Parallel processing of linear quadtrees on a mesh-connected computer, JPDC 7, 1989, l-27. 732. A. Krzyzak, S. Y. Leung, and C. Y. Suen, Reconstruction of two-dimensional patterns from Fourier descriptors, M K A 2, 1989, 123-140.
216
AZRIEL
ROSENFELD
733. A. Y. Wu, S. K. Bhaskar, and A. Rosenfeld, Parallel processing of region boundaries, PR 22, 1989, 165-172. 734. N. Kiryati and D. Maydan, Calculating geometric properties from Fourier representation, PR 22, 1989,469-475. 735. R. E. Webber and M. B. Dillencourt, Compressing quadtrees via common subtree merging, PZU 9, 1989, 193-200. 736. L. P. Cordella and G. Sanniti di Baja, Geometric properties of the union of maximal neighborhoods, T-PAMI 11, 1989,214-217. 737. J. Goutsias and D.Schonfeld, Image coding via morphological transformations: a general theory, CVPR, 178-183. 738. S. T. Huang and M. S. Tsai, A linear systolic algorithm for the connected component problem, BIT 29, 1989, 217-226. 739. T. Y. Kong, A digital fundamental group, C& G 13, 1989, 159-166. 740. W. P. Horn and D. L. Taylor, A theorem to determine the spatial containment of a point in a planar polyhedron, CVGZP 45, 1989, 106-116. 741. M. Manohar and H. K. Ramapriyan, Connected component labeling of binary images on a mesh connected massively parallel processor, CVGZP 45, 1989, 133-149. 742. V. A. Kovalevski, Finite topology as applied to image analysis, CVGZP 46, 1989, 141-161. 743. Z. C. Shih, R. C. T. Lee, and S. N. Yang, A systolic algorithm for extracting regions from a planar graph, CVGZP 47, 1989, 227-242. 744. T. Y. Kong and A. Rosenfeld, Digital topology: introduction and survey, CVGZP 48, 1989, 357-393. 745. G. Cybenko, T. G. Allen, and J. E. Polito, Practical parallel union-find algorithms for transitive closure and clustering, Zntl. J. Parallel Programming 17, 1988, 403-423. 746. R. Cypher, Hypercube and shuffle-exchange algorithms for image component labeling, .Z. Algoritfms 10, 1989, 140-150. 747. M. H. Chen and P. F. Yan, A fast algorithm to calculate the Euler number for binary images, PRL 8, 1988, 295-297. 748. R. A. Melter and A. Rosenfeld, New views of linearity and connectedness in digital geometry, PZU. 10, 1989, 9-16. 749. T. Lengauer and E. Wanke, Efficient solution of connectivity problems on hierarchically defined graphs, SLAM JC 17, 1988, 1063-1080. 750. R. Cypher, J. L. C. Sanz, and L. Snyder, An EREW PRAM algorithm for image component labeling, T-PAh4Z 11, 1989, 258-262. 751. E. Brisson, Representing geometric structures in d dimensions: topology and order, CG, 218-227. 752. V. J. Milenkovic, Verifiable implementations of geometric algorithms using finite precision arithmetic, AZ 37, 1988, 377-401. 753. A. Fleming, Geometric relationships between toleranced features, AZ 37, 1988, 403-412. 754. C. M. Hollinann, The problems of accuracy and robustness in geometric computation, Computer 22 (31, 1989, 31-41. 755. K. Sugihara, On finite-precision representations of geometric objects, ZCSS 39, 1989, 236-247. 756. D. I. Havelock, Geometric precision in noise-free digital images, T-PAMZ 11, 1989, 1065-10755. 757. V. J. Milenkovic, Robust geometric computations for vision and robotics, IUW, 764-773.
H.2. Curves, etc. 758. I. Wilf and Y. Manor, Tracking parameterized algebraic curves on raster displays, C&G l3, 1989,355-359. 759. X. Wu and J. G. Rokne, Double-step generation of ellipses, CGA 9(3), 1989, 56-69. 760. I. Galton, An efficient three-point arc algorithm, CGA 9(6), 1989, 44-49. 761. W. G. Kropatsch and H. Tockner, Detecting the straightness of digital curves in O(N) steps, CVGZP 45, 1989, l-21. 762. D. J. Walton, A note on graphics editing of curved line drawings, CVGZP 45, 1989, 61-67. 763. J. Dassow, Graph-theoretical properties and chain code picture languages, EIK 25, 1989, 423-433. 764. D. G. Lowe, Organization of smooth image curves at multiple scales, ZJCV 3, 1989, 119-130. 765. R. I. Hartley, Drawing polygons given angle sequences, ZPL 31, 1989,31-33.
IMAGE ANALYSIS AND COMPUTER
VISION:
1989
217
766. H. Ogawa, Corner detection on digital curves based on local symmetry of the shape, PR 22, 1989. 351-357. 767. A. E. Middleditch, T. W. Stacey, and S. B. Tor, Intersection algorithms for lines and circles, TOG 8, 1989, 25-40. 768. G. Farin, Curvature continuity and offsets for piecewise tonics, TOG 8, 1989, 89-99. 769. M. C. Stone and T. D. DeRose, A geometric characterization of parametric cubic curves, TOG 8, 1989, 147-163. 770. R. Sriraman, J. Koplowitz, and S. Mohan, Tree searched chain coding for subpixel reconstruction of planar curves, T-PAM1 11, 1989, 95-104. 771. X. Wu and J. Rokne, On properties of discretized convex curves, T-PAM1 11, 1989, 217-223. 772. C. H. Teh and R. T. Chin, On the detection of dominant points on digital curves, T-PAMI 11, 1989, 859-872. 773. B. Kartikeyan and A. Sarkar, Shape description by time series, T-PAMI 11, 1989, 977-984. 774. S. Biswas and S. K. Pal, Approximate coding of digital contours, T-SMC’18, 1988, 1056-1066. 775. S. Pham, Parallel, overlapped, and intersected digital straight lines, VC 4, 1988, 247-258. 776. E. Kaltofen, Computing the irreducible real factors and components of an algebraic curve, CG. 79-87. 777. S. S. Abhyankar, S. Chandrasekar, and V. Chandru, Degree complexity bounds on the intersection of algebraic curves, CG, 88-93. 778. A. Arokiasamy, Homogeneous coordinates and the principle of duality in two dimensional clipping, C& G 13, 1989, 99-100. 779. A. Margalit and G. D. Knott, An algorithm for computing the union, intersection or difference of two polygons, C& G 13, 1989, 167-183. 780. S. Forchhammer, Digital plane and grid point segments, CVGIP 47, 1989, 373-384.
H.3.
Distance, Skeletons
781. R. W. Hall, Fast parallel thinning algorithms: parallel speed and connectivity preservation, Comm. A C M 32, 1989, 124-131. 782. Z. Guo and R. W. Hall, Parallel thinning with two-subiteration algorithms, Comm. A C M 32, 1989, 359-373. 783. A. L. D. Beckers and A. W. M. Smeulders, A comment on “A note on distance transformations in digital images,” CVGIP 47, 1989, 89-91. 784. H. Beffert and R. Shinghal, Skeletonizing binary patterns on the homogeneous multiprocessor, IJPRAI 3, 1989, 207-216. 785. J. E. Bobrow, A direct minimization approach for obtaining the distance between convex polyhedra, IJRR 8 (3), 1989, 65-76. 786. R. Shonkwiler, An image algorithm for computing the Hausdortf distance efficiently in linear time, IPL 30, 1989, 87-89. 787. J. C. Culberson and P. Rudnicki, A fast algorithm for constructing trees from distance matrices, IPL 30, 1989, 215-220. 788. P. P. Das and B. N. Chatterji, Estimation of errors between Euclidean and m-neighbor distance. IS 48, 1989, l-26. 789. G. L. Scott, S. C. Turner, and A. Zisserman, Using a mixed wave-diffusion process to elicit the symmetry set, IVC 7, 1989, 63-70. 790. C. Holt and A. Stewart, A parallel thinning algorithm with fine grain subtasking, PC 10, 1989. 329-334. 791. Y. S. Chen and W. H. Hsu, A systematic approach for designing 2-subcycle and pseudo-subcycle parallel thinning algorithms, PR 22, 1989, 267-282. 792. N. G. Bourbakis, A parallel-symmetric thinning algorithm, PR 22, 1989, 387-396. 793. G. Borgefors, Distance transformations on hexagonal grids, PRL 9, 1989, 97-105. 794. P. P. Das, An algorithm for computing the number of the minimal paths in digital images, PRL 9, 1989, 107-116. 795. S. K. Pal, Fuzzy skeletonization of an image, PRL 10, 1989, 17-23. 796. P. P. Das, More on path generated digital metrics, PRL 10, 1989, 25-31. 797. P. P. Das, Metric&y preserving transforms, PRL 10, 1989, 73-76. 798. J. H. Sossa, An improved parallel algorithm for thinning digital patterns, PRL 10, 1989, 77-80.
218
AZRIEL
ROSENFELD
799. J. Mukherjee and B. N. Chatterji, Thinning of 3-D images using the Safe Point Thinning Algorithm @PTA), PRL. 10, 1989, 167-173. 800. F. Meyer, Skeletons and perceptual graphs, SP 16, 1989,335-363. 801. P. S. P. Wang and Y. Y. Zhang, A fast and flexible thinning algorithm, T-COMP 38, 1989, 741-745. 802. C. Arcelli and G. Sanniti di Baja, A one-pass two-operation process to detect the skeletal pixels on the 4-distance transform, T-PAMI 11, 1989, 411-414. 803. B. J. H. Verwer, P. W. Verbeek, and S. T. Dekker, An efficient uniform cost algorithm applied to distance transforms, T-PAMZ 11, 1989, 424-429. 804. E. Wolfson and E. L. Schwartz, Computing minimal distances on polyhedral surfaces, T-PNZ 11, 1989, 1001-1005. 805. Y. Xia, Skeletonization via the realization of the fire front’s propagation and extinction in digital binary shapes, T-PAMI 11, 1989, 1076-1086. 806. Y. S. Chen and W. H. Hsu, A 1-subcycle parallel thinning algorithm for producing perfect b-curves and obtaining isotropic skeleton of an Lshape pattern, CVPR, 208-215.
H.4. Properties, Recognition 807. W. C. Lin, C. C. Liang, and C. T. Chen, A computational model for process-grammar, AZ 38, 1989, 207-224. 808. S. S. Skiena, Problems in geometric probing, Algorithmicn 4, 1989, 599-605. 809. S. M. Thomas and Y. T. Chan, A simple approach for the estimation of circular arc center and its radius, CVGIP 45, 1989, 362-370. 810. J. A. Gualtieri, S. Baugher, and M. Werman, The visual potential: one convex polygon, CVGIP 46, 1989, 96-130. 811. G. Marola, Using symmetry for detecting and locating objects in a picture, CVGZP 46, 1989, 179-195. 812. D. Kijlzow, A. Kuba, and A. Volcic, An algorithm for reconstructing convex bodies from their projections, DCG 4, 1989, 205-237. 813. Y. T. Tsay and W. H. Tsai, Model-guided attributed string matching by split-and-merge for shape recognition, IJPRAI 3, 1989, 159-179. 814. A. Bryant and J. Bryant, Recognizing shapes in planar binary images, PR 22, 1989, 155-164. 815. C. L. Chen, Computing the convex hull of a simple polygon, PR 22, 1989, 561-565. 816. Z. Hussein, A fast approximation to a convex hull, PRL 8, 1988, 289-294. 817. (M. Zhu), S. Hasani, S. Bhattarai, and H. Singh, Pattern recognition with moment invariants on a machine vision system, PRL 9, 1989, 175-180. 818. K. S. Ray and D. Dutta Majumder, Application of differential geometry to recognize and locate partially occluded objects, PRL 9, 1989, 351-360. 819. H. I. Stern, Polygonal entropy: a convexity measure, PRL 10, 1989, 229-235. 820. R. Takiyama and N. Ono, A least square error estimation of the center and radii of concentric arcs, PRL 10, 1989, 237-242. 821. P. Seitz, The robust recognition of object primitives using local axes of symmetry, SP 18, 1989, 89-108. 822. G. Marola, On the detection of the axes of symmetry of symmetric and almost symmetric planar images, T-PAMI 11, 1989, 104-108. 823. C. Ronse, A bibliography on digital and computational convexity (1961-19881, T-PAMZ 11, 1989, 181-190. 824. J. Koplowitz and A. M. Bruckstein, Design of perimeter estimators for digitized planar shapes, T-PAMI 11, 1989,611-622. 825. C. H. Lo and H. S. Don, 3-D moment forms: their construction and application to object identification and positioning, T-PAhfZ 11, 1989, 1053-1064. 826. S. Y. Shin and T. C. Woo, An optimal algorithm for finding all visible edges in a simple polygon, T-R/l 5, 1989, 202-207.
827. G. C. Burdea and H. J. Wolfson, Solving jigsaw puzzles by a robot, TX4 5, 1989, 752-764. 828. A. Taza and C. Y. Suen, Discrimination of planar shapes using shape matrices, T-SMC 19, 1989, 1281-1289. 829. K. Rao and R. Nevatia, Descriptions of complex objects from incomplete and imperfect data, Iuw, 399-414.
IMAGE ANALYSIS AND COMPUTER
VISION:
1989
219
830. A. Khotanzad and J. H. Lu, Object recognition using a neural network and invariant Zernike features, CVPR, 200-205. 831. G. Taubin, R. M. Bolle, and D. B. Cooper, Representing and comparing shapes using shape polynomials, CVPR, 510-516. 832. P. J. Hayes and M. Leyton, Processes at discontinuities, IJCAI, 1267-1272. 833. F. J. Vasko, F. E. Wolf, and K. L. Stott, A practical solution to a fuzzy two-dimensional cutting stock problem, FSS 29, 1989,259-275. 834. X. Markenscoff and C. H. Papadimitriou, Optimum grip of a polygon, IJRR 8 (21, 1989, 17-29. 835. J. C. Trinkle and R. P. Paul, The initial grasp liftability chart, T-RA 5, 1989, 47-52.
H.5.
Motion and Path Planning;
Mapping
836. K. Sutner and W. Maass, Motion planning among time dependent obstacles, Acta Infomatica 26, 1988, 93-122. 837. J. T. Schwartz and M. Sharir, A survey of motion planning and related geometric algorithms, AZ 37, 1988, 157-169. 838. J. S. B. Mitchell, An algorithmic approach to some problems in terrain navigation, AI 37, 1988, 171-201. 839. J. Canny, Constructing roadmaps of semi-algebraic sets I: Completeness, AI 37, 1988, 203-222. 840. B. R. Donald, A geometric approach to error detection and recovery for robot motion planning with uncertainty, AI 37, 1988, 233-271. 841. C. L. Bajaj and M. S. Kim, Generation of configuration space obstacles: the case of moving algebraic curves, Algorithmica 4, 1989, 157-172. 842. M. Shairir, Algorithmic motion planning in robotics, Computer 22 (3), 1989, 9-20. 843. T. Lozano-Perez, J. L. Jones, E. Mazer, and P. A. O’Donnell, Task-level planning of pick-andplace robot motions, Computer 22(3), 1989, 21-29. 844. P. J. de Rezende, D. T. Lee, and Y. F. Wu, Rectilinear shortest paths in the presence of rectangular barriers, DCG 4, 1989, 41-53. 845. L. J. Guibas, M. Sharir, and S. Sifrony, On the general motion-planning problem with two degrees of freedom, DCG 4, 1989,491-521. 846. C. E. Buckley, A foundation for the “flexible-trajectory” approach to numeric path planning. IJRR 8 (31, 1989, 44-64. 847. B. Steer, Trajectory planning for a mobile robot, IJRR 8 (5), 1989, 3-14. 848. S. J. Buckley, Planning compliant motion strategies, IJRR 8 (5), 1989, 28-44. 849. C. W. Warren, J. C. Danos, and B. W. Mooring, An approach to manipulator path planning, IJRR 8 (5), 1989, 87-95. 850. J. S. Provan, Shortest enclosing walks and cycles in embedded graphs, IPL 30, 1989, 119-125 851. E. B. Feinberg, Characterizing the shortest path of an object among obstacles, IPL 31, 1989, 257-264. 852. M. Sharir, A note on the Papadimitriou-Silverberg algorithm for planning optimal piecewise-hnear motion of a ladder, IPL 32, 1989, 187-190. 853. B. K. Bhattacharya and J. Zorbas, Solving the two-dimensional findpath problem using a line-triangle representation of the robot, J. Algorithms 9, 1988, 449-469. 854. E. B. Feinberg and C. H. Papadimitriou, Finding feasible paths for a two-point body, J. Algorithms 10, 1989, 109-119. 855. F. Dehne, A. L. Hassenklover, and J. R. Sack, Computing the configuration space for a robot on a mesh-of-processors, PC 12, 1989, 221-231. 856. K. Fujimura and H. Samet, A hierarchical strategy for path planning among moving obstacles. T-RA 5, 1989, 61-69. 857. 0. Takahashi and R. J. Schilling, Motion planning in a plane using generalized Voronoi diagrams, T-RA 5, 1989, 143-150. 858. E. Cheung and V. J. Lumelsky, Proximity sensing in robot manipulator motion planning: system and implementation issues, T-RA 5, 1989, 740-751. 859. J. Borenstein and Y. Koren, Real-time obstacle avoidance for fast mobile robots, T-SA4C 19, 1989, 1179-1187. 860. Y. Hwang and N. Ahuja, Path planning using a potential field representation, CVPR, 569-575. 861. D. Halperin and M. H. Gvermars, Efficient motion planning for an L-shaped object, CG, 156-166.
220
AZRIEL
ROSENFELD
862. L. P. Chew and K. Kedem, Placing the largest similar copy of a convex polygon among polygonal obstacles, CG, 167-174. 863: J. Friedman, J. Hershberger, and J. Snoeyink, Compliant motion in a simple polygon, CG, 175-186. 864. A. J. Briggs, An efficient algorithm for one-step planar compliant motion planning with uncertainty, CG, 187-196. 865. E. M. Arkin, R. Connelly, and J. S. B. Mitchell, On monotone paths among obstacles, with applications to planning assemblies, CG, 334-343. 866. L. Tychonievich, D. Zaret, J. Mantegna, R. Evans, E. Muehle, and S. Martin, A maneuveringboard approach to path planning with moving obstacles, IJCAI, 1017-1021. 867. B. Zhang, L. Zhang, and T. Zhang, Motion planning of multi-joint robotic arm with topological dimension reduction method, IJCAI, 1029-1034. 868. B. Faltings, E. Baechler, and J. Primus, Reasoning about kinematic topology, IJCAI, 1331-1336. 869. A. Hemmerling, Labyrinth Problems-Labyrinth-Searching Abilities of Automata, Teubner, Leipzig, 1989. 870. A. Elfes, Using occupancy grids for mobile robot perception and navigation, Computer 22 (61, 1989,46-57. 871. Y. Roth-Tabak and R. Jain, Building an environment model using depth information, Computer 22 (6), 1989, 85-90. 872. R. C. Arkin, Motor schema-based mobile robot navigation, IJRR 8 (41, 1989, 92-112. 873. N. Ayache and 0. D. Faugeras, Maintaining representations of the environment of a mobile robot, T-RA 5, 1989, 804-819. 874. B. J. Kuipers and Y. T. Byun, A robust, qualitative method for robot spatial learning, AAAI, 774-779. 875. E. Davis, Inferring ignorance from the locality of visual perception, AAAI, 786-790 876. K. Basye, T. Dean, and J. S. Vitter, Coping with uncertainty in map learning, IJCAI, 665-668. 877. M. Asada and Y. Shirai, Building a world model for a mobile robot using dynamic semantic constraints, IJCAI, 1629-1634.
I. Color and Texture I.1. Illumination
and Color
878. R. Hall, Illumination and Color in Computer Generated Imagery, Springer, Berlin, 1988. 879. B. Funt and J. Ho, Color from black and white, ZJCV 3, 1989, 109-117. 880. W. A. Wright, A Markov random field approach to data fusion and colour segmentation, NC 7, 1989, 144-150. 881. L. B. Wolff, Material classification and separation of reflection components using polarization/ radiometric information, IUW, 232-244. 882. M. J. Daily, Color image segmentation using Markov random fields, IUW, 552-562, 1149-1151. 883. G. Healey, A parallel color algorithm for segmenting images of 3-D scenes, IUW, 1038-1042. 884. M. J. Daily, Color image segmentation using Markov random fields, CVPR, 304-312. 885. L. B. Wolff, Using polarization to separate reflection components, CVPR, 363-369. 886. L. B. Wolff and T. E. Boult, Polarization/radiometric based material classification, CVPR, 387-395. 887. D. Forsyth and A. Zisserman, Mutual illumination, CVPR, 466-473. 888. B. J. Lindbloom, Accurate color reproduction for computer graphics applications, SIGGRAPH, 117-126.
1.2. Texture: ModeIs, Synthesis H. 0. Peitgen and D. Saupe, The Science of Fractal Images, Springer, Berlin, 1988. M. Barnsley, FractaLFEverywhere, Academic Press, Boston, 1988. J. Shallit and J. Stohi, Two methods for generating fractals, C& G 13, 1989, 185-191. N. Yokoya, K. Yamamoto, and N. Funakubo, Fractal-based analysis of 3D natural surface shapes and their application to terrain modeling, CVGIP 46, 1989, 284-302. 893. P. Boulanger, A. Gagalowicz, and M. Rioux, Integration of synthetic surface relief in range images, CVGZP 47, 1989, 361-372.
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894. S. L. Stepoway and M. Christiansen, Parallel rendering of fractal surfaces, Intl J. Parallel Pmgramming 17, 1988, 43-58. 895. H. Derin and P. A. Kelly, Discrete-index Markov-type random processes, P-IEEE 77, 1989. 1485-1510. 896. P. Meer and S. Connelly, A fast parallel method for synthesis of random patterns, PR 22, 1989, 189-204. 897. S. K. Bhaskar, A. Rosenfeld, and A. Wu, Models for neighbor dependency in planar point pattens, PR 22, 1989, 533-559. 898. A. Margalit, A parallel algorithm to generate a Markov random field image on a SIMD hypercube machine, PRL 9, 1989, 263-278. 899. D. Jeulin, Morphological modeling of images by sequential random functions, SP 16, 1989. 403-431. 900. D. S. Jeong and P. M. Lapsa, Unified approach for early-phase image understanding using a general decision criterion, T-PAMZ 11, 1989, 357-371. 901. M. Boudaoud and L. F. Chaparro, Nonstationary composite modeling of images, T-SMC 19, 1989, 112-117. 902. C. A. Pickover, The use of image processing techniques in rendering maps with deterministic chaos, VC 4, 1988, 271-276. 903. C. C. Chen and R. C. Dubes, Experiments in fitting discrete Markov random fields to textures. CVPR, 298-303. 904. X. G. Viennot, G. Eyrolles, N. Janey, and D. Arques, Combinatorial analysis of ramified patterns and computer imagery of trees, SIGGRAPH, 31-40. 905. F. K. Musgrave, C. E. Kolb, and R. S. Mice, The synthesis and rendering of fractal terrains. SIGGRAPH, 41-50. 906. R. Szeliski and D. Terzopoulos, From splines to fractals, SIGGRAPH, 51-60. 907. N. Greene, Voxel space automata: modeling with stochastic growth processes in voxel space. SIGGRAPH, 175-184. 908. K. Perlin and E. M. Hoffert, Hypertexture, SIGGRAPH, 253-262. 909. J. P. Lewis, Algorithms for solid noise synthesis, SIGGRAPH, 263-270. 910. J. T. Kajiya and T. L. Kay, Rendering fur with three dimensional textures, SIGGRAPH, 271-280.
1.3. Texture: Desctiption 911. I. Fogel and D. Sagi, Gabor filters as texture discriminator, BC 61, 1989, 103-113. 912. R. Vistnes, Texture models and image measures for texture discrimination, IJCV 3, 1989, 313-336. 913. J. Garding, Properties of fractal intensity surfaces, PRL 8, 1988, 319-324. 914. P. Cohen, C. T. LeDinh, and V. Lacasse, Classification of natural textures by means of two-dimensional orthogonal masks, T-ASP 37, 1989, 125-128. 915. Z. Liu and Y. Attikiouzel, Two-dimensional linear prediction model-based decorrelation method, T-PAMI 11, 1989, 661-665.
916. M. Amadasun and R. King, Textural features corresponding to textural properties, T-SMC 19, 1989, 1264-1274. 917. L. G. C. Hamey and T. Kanade, Computer analysis of regular repetitive textures, IUW, 1076-1088. 918. A. R. Rao and B. G. Schunck, Computing oriented texture fields, CVPR, 61-68.
1.4. Texture: Segmentation 919. K. Iwama, Merging regions across feature maps in texture segmentation, BC 61, 1989, 295-302. 920. J. M. Keller, S. Chen, and R. M. Crownover, Texture description and segmentation through fractal geometry, CVGZP 45, 1989, 150-166. 921. J. Y. Hsiao and A. A. Sawchuk, Unsupervised textured image segmentation using feature smoothing and probabilistic relaxation techniques, CVGZP 48, 1989, 1-21. 922. C. A. Sher and A. Rosenfeld, Detecting and extracting compact textured regions using pyramids, ZVC 7, 1989, 129-134. 923. R. L. Kashyap and K. B. Eom, Texture boundary detection based on the long correlation model, T-PAM 11, 1989, 58-67.
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924. A. Khotanzad, Unsupervised segmentation of textured images by edge detection in multidimensional features, T-PAMI 11, 1989, 414-421. 925. M. C. K. Yang and C. C. Yang, Image enhancement for segmentation by self-induced autoregressive filtering, T-PAMZ 11, 1989, 655-661. 926. M. Unser and M. ,Eden, Multiresolution feature extraction and selection for texture segmentation, T-PAMZ 11, 1989, 717-728. 927. J. Y. Hsiao and A. A. Sawchuk, Supervised textured image segmentation using feature smoothing and probabilistic relaxation techniques, T-PAMZ 11, 1989, 1279-1292. 928. A. Perry and D. G. Lowe, Segmentation of textured images, CVPR, 319-325. 929. J. Malik and P. Perona, A computational model of texture segmentation, CVPR, 326-332.
J. Three-Dimensional J.1. 30 Acquisition,
Scene Ana&s
etc.
930. P. Besl, Surfaces in Range Image Understanding, Springer, Berlin, 1988. 931. A. Jain and R. Jain, Range Image Understanding, Springer, Berlin, 1989.
932. R. Jain and A. K. Jain, Report on Range Image Understanding Workshop, East Lansing, Michigan, March 21-23, 1988, MEA 2, 1989, 45-60. 933. R. A. Grupen, T. C. Henderson, and I. D. McCammon, A survey of general-purpose manipulation, ZJRR 8 (11, 1989, 38-62. 934. H. R. Nicholls and M. H. Lee, A survey of robot tactile sensing technology, ZJZU? 8 (31, 1989, 3-30. 935. A. S. Acampora and J. H. Winters, Three-dimensional ultrasonic vision for robotic applications, T-PAMZ 11, 1989, 291-303. 936. G. Hu and G. Stockman, 3-D surface solution using structured light and constraint propagation, T-PAMZ 11, 1989, 390-402. 937. N. Shrikhande and G. Stockman, Surface orientation from a projected grid, T-PAMZ 11, 1989, 650-655. 938. M. Matsuki and T. Ueda, A real-time sectional image measuring system using time sequentially coded grating method, T-PAMZ 11, 1989, 1225-1228. 939. Y. Srinivasan and R. Lumia, A pseudo-interferometric laser range finder for robot applications, T-Z&4 5, 1989, 98-105. 940. T. Tsujimura and T. Yabuta, Object detection by tactile sensing method employing force-torque information, T-RA 5, 1989, 444-450. 941. K. Pribadi, J. S. Bay, and H. Hemami, Exploration and dynamic shape estimation by a robot probe, T-SMC 19, 1989, 840-846. 942. Y. F. Wang and P. Liang, A new method for computing intrinsic surface properties, CVPR, 235-240. 943. A. Pentland, T. Darrell, M. Turk, and W. Huang, A simple, real-time range camera, CVPR, 256-261. 944. C. M. Bastuschek, Techniques for real-time generation of range images, CVPR, 262-268. 945. T. L. Hwang, J. J. Clark, and A. L. Yuille, A depth recovery algorithm using defocus information, CVPR, 476-482. 946. R. L. Keizer and S. M. Dunn, Marked grid labeling, CVPR, 612-617. 947. P. K. Allen and P. Michelman, Acquisition and interpretation of 3-D sensor data from touch, WI3DS, 33-40. 948. M. Rioux, F. Blais, J. A. Beraldin, and P. Boulanger, Range imaging sensors development at NRC Laboratories, WDDS, 154-160. 949. R. W.‘Taylor, M. Savini, and A. P. Reeves, Fast segmentation of range imagery into planar regions, CVGZP 45, 1989, 42-60. 950. X. Y. Jiang and H. Bunke, Segmentation of the needle map of objects with curved surfaces, PZU 10, 1989, 181-187. 9.51. P. J. Flynn and A. K. Jain, On reliable curvature estimation, CVPR, 110-116. 952. P. Grossmann, From 3D line segments to objects and spaces, CVPR, 216-221. 953. F. Mokhtarian, Fingerprint theorems for curvature and torsion zero-crossings, CVPR, 269-275. 954. G. D. Godin and M. D. Levine, Structured edge map of curved objects in a range image, CVPR, 276-281.
IMAGE ANALYSIS AND COMPUTER
VISION: 1989
22.3
955. G. Hu and G. Stockman, Representation and segmentation of a cluttered scene using fused edge and surface data, CVPR, 313-318. 956. J. O’Rourke and C. Schevon, Computing the geodesic diameter of a 3-polytope, CG, 370-379. 957. R. R. Karinthi and D. S. Nau, Using a feature algebra for reasoning about geometric feature interactions, IJCAI, 1219-1224. 958. D. Gordon and J. K. Udupa, Fast surface tracking in three-dimensional binary images, CVGIP 45, 1989,196-216. 959. D. J. Rossi, A. S. Willsky, and D. M. Spielman, Object shape estimation from tomographic measurements-a performance analysis, S P 18, 1989, 63-87.
960. R. L. (S) Drysdale III, R. B. Jerard, B. Schaudt, and K. Hauck, Discrete simulation of NC machining, Algorithmica 4, 1989, 33-60. 961. V. D. Nguyen, Constructing stable grasps, IJRR 8 (11, 1989, 26-37. 962. M. R. Cutkosky, On grasp choice, grasp models, and the design of hands for manufacturing tasks, T-h54 5, 1989, 269-279.
963. B. Mishra and N. Silver, Some discussion of static gripping and its stability, T-SMC 19, 1989, 783-796. 964. M. Mehdian and H. Rahnejat, A sensory gripper using tactile sensors for object recognition, orientation control, and stable manipulation, T-SMC 19, 1989, 1250-1261. 965. S. A. Stansfield, Reasoning about grasping, AAAI, 768-773.
J. 2. Recovery 966. J. Aloimonos and D. Shulman, Integration of Visual Modules-An Extension of the Marr Paradigm, Academic Press, Boston, 1989. 967. B. K. P. Horn and M. J. Brooks, eds., Shape from Shading, MIT Press, Cambridge, MA, 1989. 968. R. Horaud and M. Brady, On the geometric interpretation of image contours, AI 37, 1988, 333-353. 969. K. Kanatani and T. C. Chou, Shape from texture: general principle, AZ 38, 1989, l-48. 970. A. L. Yuille, Zero crossings on lines of curvature, CVGZP 45, 1989, 68-87. 971. Lavakusha, A. K. Pujari, and P. G. Reddy, Linear octrees by volume intersection, CVGIP 45, 1989,371-379. 972. M. A. Penna, Local and semi-local shape from shading for a simple perspective image of a smooth object, CVGIP 46, 1989, 346-366.
973. S. Kamata, S. Ishikawa, and K. Kato, Reconstructing an edge on a polyhedron using an optimization method, CVGIP 47, 1989, 92-104. 974. W. Whiteley, A matroid on hypergraphs, with applications to scene analysis and geometry, DCG 4, 1989,75-95. 975. T. Shakunaga and H. Kaneko, Perspective angle transform: principle of shape from angles, I&X’ 3, 1989 239-254. 976. K. Kanatani, Reconstruction of consistent shape from inconsistent data: optimization of 2fD sketches, IJCV 3, 1989, 261-292. 977. A. Zisserman, P. Giblin, and A. Blake, The information available to a moving observer from
specularities, NC 7, 1989, 38-42. 978. J. (Y.) Aloimonos and D. Shulman, Learning early-vision computations, JOSA A6, 1989. 908-919. 979. L. Quan and R. Mohr, Determining perspective structures using hierarchical Hough transform. PRL 9, 1989, 279-286. 980. J. T. Lapreste, P. Pineau, and M. Richetin, About the integrability constraint in a shape-fromshading algorithm, PRL 10, 1989, 53-60. 981. J. G. Luu, Shape normalization through compacting, PRL 10, 1989, 243-250. 982. K. Henriksen and J. Arnspang, Direct determination of the orientation of a translating 3D straight line, PRL 10, 1989, 251-258. 983. J. Y. Aloimonos, Unifying shading and texture through an active observer, Proc. Roy. Sot. London B 238, 1989, 25-37. 984. N. Ahuja and J. Veenstra, Generating octrees from object silhouettes in orthographic views. T-PAMI 11, 1989, 137-149. 985. F. P. Ferrie and M. D. Levine, Where and why local shading analysis works, T-PAMI 11, 1989,
198-206.
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986. K. Kanatani, 3D Euclidean versus 2D non-Euclidean: two approaches to 3D recovery from images, T-PAMI 11,1989,329-332. 987. M. A. Penna, A shape from shading analysis for a single perspective image of a polyhedron, T-PAMZ 11, 1989,545-554. 988. J. Malik and D. Maydan, Recovering three-dimensional shape from a single image of curved objects, T-PAMI 11, 1989, 555-566. 989. B. Cemuschi-Frias, D. B. Cooper, Y. P. Hung, and P. N. Belhumeur, Toward a model-based Bayesian theory for estimating and recognizing parameterized 3-D objects using two or more images taken from different positions, T-PAMI 11, 1989, 1028-1052. 990. V. S. Nalwa, Line-drawing interpretation: bilateral symmetry, T-PAMZ 11, 1989, 1117-1120. 991. D. Blostein and N. Ahuja, Shape from texture: integrating texture-element extraction and surface estimation, T-PAMI 11, 1989, 1233-1251. 992. Y. F. Wang and J. K. Aggarwal, Integration of active and passive sensing techniques for representing three-dimensional objects, T-RA 5, 1989, 460-471. 993. D. Raviv, Y. H. Pao, and K. A. Loparo, Reconstruction of three-dimensional surfaces from two-dimensional binary images, T-Z&4 5, 1989, 701-710. 994. N. Kawabata, Three-dimensional interpretation of perspective images, T-SMC 19, 1989,117-123. 995. D. Raviv, Y. H. Pao, and K. A. Loparo, Segmentation between overlapping parts: the moving shadows approach, T-SMC 19, 1989, 880-883. 996. T. Tanaka, S. Naito, and T. Takahishi, Generalized symmetry and its application to 3D shape generation, 1/C 5, 1989, 83-94. 997. A. Pentland, On the extraction of shape information from shading, A&Q 826-830. 998. J. Y. Aloimonos, Unification and integration of visual modules: an extension of the Marr paradigm, IUW, 507-551. 999. S. K. Nayar, K. Ikeuchi, and T. Kanade, Extracting shape and reflectance of hybrid surfaces by photometric sampling, IUW, 563-583. 1000. B. K. P. Horn, Height and gradient from shading, IUW, 584-595. 1001. F. Ulupinar and R. Nevatia, Constraints for interpretation of perspective images, IUW, 882-892. 1002. A. D. Gross and T. E. Boult, Straight homogeneous generalized cylinders: analysis of reflectance properties and a necessary condition for class membership, IUW, 967-973. 1003. L. B. Wolff, Shape understanding from Lambertian photometric flow fields, IUW, 974-982. 1004. M. Hatzitheodorou, The derivation of 3-D surface shape from shadows, IUW, 1012-1020. 1005. B. V. H. Saxberg, An application of dynamical systems theory to shape from shading, IUW, 1089-1104. 1006. H. D. Tagare and R. J. P. deFiguereido, A theory of photometric stereo for a general class of reflectance maps, CVPR, 38-45. 1007. L. B. Wolff, Shape understanding from Lambertian photometric flow fields, CVPR, 46-52. 1008. K. Hartt and M. Carlotto, A method for shape-from-shading using multiple images acquired under different viewing and lighting conditions, CVPR, 53-60. 1009. G. Ron and S. Peleg, Multiresolution shape from shading, CVPR, 350-355. 1010. R. M. Haralick, Monocular vision using inverse perspective projection geometry: analytic relations, CVPR, 370-378. 1011. M. Richetin, M. Dhome, and J. T. Lapreste, Inverse perspective transform from zero-curvature curve points application to the location of some generalized cylinders, CVPR, 517-522. 1012. P. Kube, Likely local shape, CVPR, 529-534. 1013. G. Xu and S. Tsuji, Three-dimensional interpretation of quadrilaterals, IJCAI, 1610-1616. 1014. P. Bellutta, G. Collini, A. Verri, and V. Torre, 3D visual information from vanishing points, WI3DS, 41-49. 1015. C. I. Connolly and J. R. Stenstrom, 3D scene reconstruction from multiple intensity images, WISDS, 124-130.
J.3. Shape and Models 1016. J. J. Koenderink, Solid Shape, MIT Press, Cambridge, MA, 1989. 1017. B. A. Barsky, Computer Graphics and Geometric Modeling using Beta-Splines, Springer, Berlin, 1988. 1018. M. Mantyla, An Zntroduction to Solid Modeling, Computer Science Press, Rockville, MD, 1988. 1019. F. Yamaguchi, Curves and Surfaces in Computer-Aided Geomerric Design, Springer, Berlin, 1988.
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VISION:
1989
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1020. M. J. Wozny, H. W. McLaughlin, and J. L. Encarnacao, eds., Geometric Modeling for CAD Applications (IFIP Working Group, Troy, NY, May 12-16, 1988), North-Holland, Amsterdam, 1988. 1021. C. M. Hofhnann, Geometric and Solid Modeling: An Introduction, Morgan Kaufmann, San Mateo, CA, 1989. 1022. T. Lyche and L. L. Schumaker, Mathematical Me&oak in Computer Aided Geometric Design, Academic Press, Boston, 1989. 1023. (B. Q. St11and (D. Y. Liu), Computational Geometry-Curve and Su&ce Modeling, Academic Press, Boston, 1989. 1024. SIAM Conference on Geometric Design, Tempe, AZ, November 6-10, 1989. 1025. C. Hoffmann and J. Hopcroft, The geometry of projective blending surfaces, AZ 37, 1988. 357-316.
1026. I. Navazo, Extended octtree representation of general solids with plane faces: model structure and algorithms, C& G 13, 1989, 5-16. 1027. C. Sobhanpanah, Extension of a boundary representation technique for the description of N dimensional polytopes, C& G 13, 1989, 17-23. 1028. C. B. Millham and J. L. Zhang, A linear pivoting heuristic procedure for computing the curve of intersection of two bicubic surface patches, C& G 13, 1989, 25-38. 1029. D. Geist and M. W. Vannier, PC-based 3-D reconstruction of medical images, C& G 13, 1989, 135-143. 1030. B. Sinclair, A. G. Hannam, A. A. Lowe, and W. W. Wood, Complex contour organization for surface reconstruction, C& G 13, 1989,311-319. 1031. M. Roche, Defining a faceted generalized cylinder by projections of cross sections, C& G 13, 1989, 349-354. 1032. G. Aumann, Approximation development of skew ruled surfaces, C& G 13, 1989, 361-366. 1033. V. Akman and W. R. Franklin, Representing objects as rays, or how to pile up an octree?, C& G 13, 1989,373-379.
1034. S. E. Chen and R. E. Parent, Shape averaging and its applications to industrial design, CGA 9 (11, 1989, 47-54. 1035. C. Mirolo and E. Pagello, A solid modeling system for robot action planning, CGA 9 (11, 1989, 55-69. 1036. G. R. Beacon, J. R. Dodsworth, S. E. Howe, R. G. Oliver, and A. Saia, Boundary evaluation
using inner and outer sets: the ISOS method, CGA 9 (21, 1989, 39-51. 1037. G. Farin and N. Sapidis, Curvature and the fairness of cures and surfaces, CGA 9 (2), 1989, 52-57.
1038. L. De Floriani, A pyramidal data structure for triangle-based surface description, CGA 9 (21, 1989, 67-78. 1039. D. J. Filip and T. W. Ball, Procedurally representing lofted surfaces, CGA 9 (6), 1989, 27-33. 1040. C. M. Hoffmann, J. E. Hopcroft, and M. S. Karasick, Robust set operations on polyhedral solids. CGA 9 (6), 1989, 50-59. 1041. L. De Floriani, B. Falcidieno, and C. Pienovi, Structured graph representation of a hierarchical triangulation, CVGZP 45, 1989, 215-226. 1042. K. Tang, On the intersection of a set of direction cones, CVGIP 45, 1989, 357-361. 1043. G. M. Radack and N. I. Badler, Local matching of surfaces using a boundary-centered radial decomposition, CVGIP 45, 1989,380-396. 1044. M. Karasick, The same-object problem for polyhedral solids, CVGIP 46, 1989, 22-36. 1045. H. Samet, Neighbor finding in images represented by octrees, CVGIP 46, 1989,367-386. 1046. B. Falcidieno and F. Giannini, Automatic recognition and representation of shape-based features in a geometric modeling system, CVGZP 48, 1989, 93-123. 1047. W. C. Lin, S. Y. Chen, and C. T. Chen, A new surface interpolation technique for reconstructing 3D objects from serial cross-sections, CVGIP 48, 1989, 124-143. 1048. V. S. Nalwa, Representing oriented piecewise C2 surfaces, IJCV 3, 1989, 131-153. 1049. S. Cameron, Efficient intersection tests for objects defined constructively, IJRR 8 (11, 1989, 3-25. 1050. J. M. Selig and J. Rooney, Reuleaux pairs and surfaces that cannot be gripped, IJRR 8 (51, 1989, 79-87. 1051. P. Grossmann, Compact-a
surface representation scheme, IVC 7, 1989, 115-121.
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1052. F. Macias-Garza, K. R. Diller, A. C. Bovik, S. J. Agganval, and J. K. Aggarwal, Obtaining a solid model from optical serial sections, PR 22, 1989, 577-586. 1053. S. Dellepiane, S. B. Serpico, and G. Vemazza, A framework for processing and interpretation of three-dimensional signals from multislices, SP 18, 1989, 239-258. 1054. J. R. Rossignac and H. B. Voelcker, Active zones in CSG for accelerating boundary evaluation, redundancy elimination, interference detection, and shading algorithms, TOG 8, 1989, 51-87. 1055. D. J. Filip, Blending parametric surfaces, TOG 8, 1989, 164-173. 1056. R. T. Farouki, C. A. Neff, and M. A. O’Connor, Automatic parsing of degenerate quadric-surface intersections, TOG 8, 1989, 174-203. 1057. C. T. Loop and T. D. DeRose, A multisided generalization of Bezier surfaces, TOG 8, 1989, 204-234.
1058. F. L. Bookstein, Principal warps: thin-plate splines and the decomposition of deformations, T-PAMZ 11, 1989, 567-585. 1059. L. De Floriani, Feature extraction from boundary models of three-dimensional objects, T-PAMZ 11, 1989, 785-798. 1060. J. Ponce, D. Chelberg, and W. B. Mann, Invariant properties of straight homogeneous generalized cylinders and their contours, T-PAMI 11, 1989, 951-966. 1061. K. R. Vemuri, S. I. Oh, and R. A. Miller, Topology-based geometry representation to support geometric reasoning, T-SMC 19, 1989, 175-187. 1062. D. Terzopoulos and K. Fleischer, Deformable models, k’C 4, 1988, 306-331. 1063. D. Pletinckx, Quatemion calculus as a basic tool in computer graphics, VC 5, 1989, 2-13. 1064. B. Wyvill and G. Wyvill, Field functions for implicit surfaces, VC 5, 1989, 75-82. 1065. M. Kosters, Quadradic blending surfaces for complex corners, VC 5, 1989, 134-146. 1066. R. Waltzman, Geometric problem solving by machine visualization, IUW, 353-354. 1067. J. L. Mundy, P. Vrobel, and R. Joynson, Constraint-based modeling, IUW, 425-442. 1068. C. I. Connolly, D. Kapur, J. L. Mundy, and R. Weiss, GeoMeter: a system for modeling and algebraic manipulation, IUW, 797-804. 1069. K. Bowyer, D. Eggert, J. Stewman, and L. Stark, Developing the aspect graph representation for use in image understanding, IUW, 831-849. 1070. C. L. Lo and H. S. Don, Representation and recognition of 3-D curves, CVPR, 523-528. 1071. S. W. Chen, and G. Stockman, Object wings-21-D primitives for 3-D recognition, CVPR, 535-540.
1072. D. Eggert and K. Bowyer, Computing the orthographic projection aspect graph of solids of revolution, WUDS, 102-108. 1073. T. Sripradisvarakul and R. Jain, Generating aspect graphs for curved objects, WI3DS, 109-115. 1074. D. J. Kriegman and J. Ponce, Computing exact aspect graphs of curved objects: solids of revolution, WI3DS, 116-122. 1075. A. Gupta, L. Bogoni, and R. Bajcsy, Quantitative and qualitative measures for the evaluation of the superquadric models, WI3DS, 162-169. 1076. F. P. Ferrie, J. Lagarde, and P. Whaite, Darboux frames, snakes, and super-quadrics: geometry from the bottom up, WI3DS, 170-176. 1077. H. Lu, L. G. Shapiro, and 0. I. Camps, A relational pyramid approach to view class determination, WI3DS, 177-183. 1078. A. H. Barr, Topics in Physical!v Based Modeling, Addison-Wesley, Reading, MA, 1989. 1079. F. Gardin and.B. Meltzer, Analogical representations of naive physics, AI 38, 1989, 139-159. 1080. G. Miller and A. Pearce, Globular dynamics: a connected particle system for animating viscous fluids, Cd? G 13, 1989, 305-309. 1081. J. Wilhelms, M. Moore, and R. Skinner, Dynamic animation: interaction and control, VC 4, 1988, 283-295. 1082. P. M. Isaacs and M. F. Cohen, Mixed methods for complex kinematic constraints in dynamic figure animation, VC 4, 1988, 296-305. 1083. D. R. Haumann and R. E. Parent, The behavioral test-bed: obtaining complex behavior from simple rules, 1/C 4, 1988, 332-347. 1084. B. Arnaldi, G. Dumont, and G. Hegron, Dynamics and unification of animation control, VC 5, 1989, 22-31. 1085. A. Pentland and J. Williams, Good vibrations: model dynamics for graphics and animation, SIGGRAPH, 215-222.
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1086. D. Baroff, Analytical methods for dynamic simulation of non-penetrating rigid bodies, SIGGRAPH, 223-232. 1087. A. Pentland and J. Williams, Perception of non-rigid motion: inference of shape, material and force, IJCAI, 1565-1570. 1088. L. Joskowicz and S. Addanki, From kinematics to shape: an approach to innovative design, AAAI,
347-352.
J.4. Image Synthesis 1089. E. L. Fiume, The Mathematical Structure of Raster Graphics, Academic Press, Boston, 1989. 1090. A. Glassner, An Introduction to Ray Tracing, Academic Press, Boston, 1989. 1091. S. Upstill, The Rendetman Companion, Addison-Wesley, Reading, MA, 1989. 1092. A. Kaufman, guest ed., Special Topic: 3D Voxel-Based Graphics, C& G 13 (21, 1989, 133-166. 1093. J. Sanchez-Reyes, Laser printers for rendering surfaces, C& G 13, 1989, 49-54. 1094. G. J. Jense and D. P. Huijsmans, Interactive voxel-based graphics for 3D reconstruction of biological structures, C& G 13, 1989, 145-150. 1095. L. Alvisi and G. Casciola, On the Two Array Mask hidden-line algorithm, C&G 13, 1989, 193-206. 1096. T. Theoharis and I. Page, Polygon rendering on a dual-paradigm parallel processor, C& G 13, 1989, 207-216. 1097. I. Gargantini, G. Schrack, and H. H. Atkinson, Adaptive display of linear octrees, C& G 13. 1989, 337-343. 1098. E. Nakamae, T. Ishizaki, T. Nishita, and S. Takita, Cornpositing digital images with antialiasing and various shading effects, CGA 9 (21, 1989, 21-29. 1099. P. K. Robertson, Spatial transformations for rapid scan-line surface shadowing, CGA 9 (2), 1989, 30-38.
1100. J. Goldfeather, S. Molnar, G. Turk, and H. Fuchs, Near real-time CSG rendering using tree normalization and geometric pruning, CGA 9 (3), 1989, 20-28. 1101. A. Mammen, Transparency and antialiasing algorithms implemented with the virtual pixel maps technique, CGA 9 (4), 1989, 43-55. 1102. S. A. Green and D. J. Paddon, Exploiting coherence for multiprocessor ray tracing, CGA 9 (6). 1989, 12-26. 1103. K. A. Frenkel, Volume rendering, Comm. ACM 32, 1989, 426-435. 1104. J. K. Udupa and G. T. Herman, Volume rendering versus surface rendering, Comm. ACM 32, 1989, 1364-1367. 1105. L. S. Chen, and M. R. Sontag, Representation, display, and manipulation of 3D digital scenes and their medical applications, CVGZP 48, 1989, 190-216. 1106. E. Fiume, A mathematical semantics of rendering I: Ideal rendering, CVGZP 48, 1989, 281-303. 1107. X. Yuan, T. L. Kunii, N. Inamoto, and L. Sun, GemstoneFire: adaptive dispersive ray tracing of polyhedrons, VC 4, 1988,259-270. 1108. T. Priol and K. Bouatouch, Static load balancing for a parallel ray tracing on a MIMD hypercube, VC 5, 1989, 109-119. 1109. J. Bu and E. F. Deprettere, A VLSI system architecture for high-speed radiative transfer 3D image synthesis, VC 5, 1989, 121-133. 1110. W. F. Bronsvoort, P. R. van Nieuwenhuizen, and F. H. Post, Display of profiled sweep objects, VC 5, 1989, 147-157. 1111. N. Max, Smooth appearance for polygonal surface, VC 5, 160-173. 1112. M. S. Paterson and F. F. Yao, Binary partitions with applications to hidden-surface removal and solid modelling, CG, 23-32. 1113. J. P. Gourret, N. Magnenat Thalmann, and D. Thalmann, Simulation of object and human skin deformations in a grasping task, SIGGRAPH, 21-30. 1114. C. Buckalew and D. Fussell, Illumination networks: fast realistic rendering with general reflectance functions, SIGGRAPH, 89-98. 1115. N. Chin and S. Feiner, Near real-time shadow generation using BSP trees, SIGGRAPH, 99-106. 1116. A. Rockwood, K. Heaton, and T. Davis, Real-time rendering of trimmed surfaces, SIGGRAPH. 107-116. 1117. T. W. Sederberg and A. K. Zundel, Scan line display of algebraic surfaces, SIGGRAPH, 147-156.
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1118. S. L. Chang, M. Shantz, and R. Rocchetti, Rendering cubic curves and surfaces with integer adaptive forward differencing, SIGGRAPH, 157-166. 1119. R. S. Gallagher and J. C. Nagtegaal, An efficient 3-D visualization technique for finite element models and other coarse volumes, SIGGRAPH, 185-194. 1120. J. Painter and K. Sloan, Antialiased ray tracing by adaptive progressive refinement, SIGGRAPH, 281-288. 1121. J. C. Hart, D. J. Sandin, and L. H. Kauffman, Ray tracing deterministic 3-D fractals, SIGGRAPH, 289-296. 1122. D. Kalra and A. H. Barr, Guaranteed ray intersections with implicit surfaces, SIGGRAPH, 297-306.
1123. C. H. Sequein and E. K. Smyrl, Parameterized ray tracing, SIGGRAPH, 307-314. 1124. J. R. Wallace, K. A. Ehnquist, and E. A. Haines, A ray tracing algorithm for progressive radios@, SIGGRAPH, 315-324. 1125. D. R. Baum, H. E. Rushmeier, and J. M. Winget, Improving radios@ solutions through the use of analytically determined form-factors, SIGGRAPH, 325-334. 1126. F. Sillion and C. Puech, A general two-pass method integrating specular and diffuse reflection, SIGGRAPH, 335-344. 1127. K. Mulmuley, An efficient algorithm for hidden surface removal, SIGGRAPH, 379-388. 1128. C. Oh, N. Nandhakumar, and J. K. Aggarwal, Integrated modelling of thermal and visual image generation, CVPR, 356-362.
J.5. Recognition 1129. A. K. Jain, ed., Real-Time Object Measurement and Classijication, Springer, Berlin, 1988. 1130. R. B. Fisher, From Surfaces to Objects-Computer V7ion and Three-Dimensional Scene Analysis, Wiley, Chichester, UK, 1989. 1131. J. E. W. Mayhew and J. P. Frisby, 3D Model Recognition from Stereoscopic Cues, MIT Press, Cambridge, MA, 1989. 1132. S. B. Pollard, T. P. Pridmore, J. Porrill, J. E. W. Mayhew, and J. P. Frisby, Geometrical modeling from multiple stereo views, ZJRR 8 (41, 1989, 3-32. 1133. A. D. Worrall, K. D. Baker, and G. D. Sullivan, Model based perspective inversion, 17/C 7, 1989, 17-23. 1134. D. Holder and H. Buxton, Polyhedral object recognition with sparse data in SIMD processing mode, NC 7, 1989,71-78. 1135. M. C. Yang and W. H. Tsai, Recognition of single 3D curved objects using 2D cross-sectional slice shapes, NC 7, 1989, 210-216. 1136. B. Bhanu and L. A. Nuttall, Recognition of 3-D objects in range images using a Butterfly multiprocessor, PR 22, 1989, 49-64. 1137. K. C. Hung, R. N. Chiou, C. N. Shyi, J. Y. Lee, and C. H. Chen, Polyhedron reconstruction using three-view analysis, PR 22, 1989, 231-246. 1138. I. Wilf and Y. Manor, Multiple-view model-based inspection of quadric objects, PZU 10, 1989, 33-38.
1139. A. K C. Wong, S. W. Lu, and M. Riouz, Recognition and shape synthesis of 3-D objects based on attributed hypergraphs, T-PAMZ 11, 1989, 279-290. 1140. C. H. Chien and J. K. Aggarwal, Model construction and shape recognition from occluding contours, T-PAMZ 11, 1989,372-389. 1141. A. P. Reeves and R. W. Taylor, Identification of three-dimensional objects using range information, T-PAMZ 11, 1989, 403-410. 1142. H.,Wechsler and G. L. Zimmerman, Distributed associative memory (DAM) for bin-picking, T-PAMZ 11, 1989, 814-822.
1143. T. J. Fan, C. Medioni, and R. Nevatia, Recognizing 3-D objects using surface descriptions, T-PAMZ 11, 1989, 1140-1157. 1144. R. Krishnapuram and D. Casasent, Determination of three-dimensional object location and orientation from range images, T-PAMZ 11, 1989, 1158-1167. 1145. C. Hansen and T. C. Henderson, CAGD-based computer vision, T-PAMZ 11, 1989, 1187-1193. 1146. D. B. Goldgof, T. S. Huang, and H. Lee, A curvature-based approach to terrain recognition, T-PAMZ 11, 1989, 1213-1217.
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VISION: 1989
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1147. C. Gurwicz and M. L. Overton, A globally convergent algorithm for minimizing over the rotation group of quadratic forms, T-PAM 11, 1989, 1228-1232. 1148. M. Dhome, M. Richetin, J. T. Lapreste, and G. Rives, Determination of the attitude of 3-D objects from a single perspective view, T-PAMZ 11, 1989, 1265-1278. 1149. J. Jurczyk and K. A. Loparo, Mathematical transforms and correlation techniques for object recognition using tactile data, T-M 5, 1989, 359-362. 1150. J. W. Roach, P. K. Paripati, and M. Wade, Model-based object recognition using a large-field passive tactile sensor, T-WC 19, 1989, 846-853. 1151. R. W. Taylor and A. P. Reeves, Classification quality assessment for a generalized model-based object identification system, T-SK 19, 1989, 861-866. 1152. T. 0. Binford, Spatial understanding: the SUCCESSOR System, IUW, 12-20. 1153. J. Ponce and D. J. Kriegman, On recognizing and positioning curved 3D objects from image contours, IUW, 461-470. 1154. T. M. Breuel, Adaptive model base indexing, IUW, 805-814. 1155. D. Cyrluk and D. Kapur, Reasoning about nonlinear inequality constraints: a multi-level approach, IUW, 904-915. 1156. A. J. Heller and J. R. Stenstrom, Verification of recognition and alignment hypotheses by means of edge verification statistics, IUW, 957-966. 1157. D. W. Thompson, Edge based transform refinement, IUW, 1070-1075. 1158. Y. Yacoob and Y. I. Gold, 3D object recognition via simulated particles diffusion, CVPR, 442-449.
1159. K. Ikeuchi and K. S. Hong, Determining linear shape change: toward automatic generation of object recognition programs, CVPR, 450-457. 1160. S. A. Hutchinson, R. I. Cromwell, and A. C. Kak, Applying uncertainty reasoning to model based object recognition, CVPR, 541-548. 1161. R. M. Bolle, A. Califano, R. Kjeldsen, and R. W. Taylor, Visual recognition using concurrent and layered parameter networks, CVPR, 625-631. 1162. R. Kjeldsen, R. M. Bolle, A. Califano, and R. W. Taylor, A homogeneous framework for visual recognition, IJCAI, 1578-1584. 1163. J. Ponce and D. J. Kriegman, On recognizing and positioning curved 3D objects from image contours, WI3DS, 61-67. 1164. R. Bergevin and M. D. Levine, Generic object recognition: building coarse descriptions from line drawings, WI3DS, 68-74. 1165. S. Lee and H. S. Hahn, Object recognition and localization using optical proximity sensor system: polyhedral case, WI3DS, 75-81. 1166. P. G. Mulgaonkar, C. K. Cowan, and J. DeCurtins, Scene description using range data, WI3DS. 138-144.
J.6. Miscellaneous 1167. E. L. Walker and M. Herman, Geometric reasoning for constructing 3D scene descriptions from images, AZ 37, 1988, 275-290. 1168. M. Barry, D. Cyrluk, D. Kapur, J. Mundy, and V. D. Nguyen, A multi-level geometric reasoning system for vision, AZ 37, 1988, 291-332. 1169. J. Raczkowsky and K. H. Mittenbuehler, Simulation of cameras in robot applications, CGA 9 (1). 1989, 16-25. 1170. K. Ikeuchi and T. Kanade, Modeling sensors: toward automatic generation of object recognition program, CVGZP 48, 1989, 50-79. 1171. P. K. Allen, Integrating vision and touch for object recognition tasks, ZJRR 7 (61, 1988, 15-33. 1172. S. Shekhar, 0. Khatib, and M. Shimojo, Object localization with multiple sensors, ZJZtR 7 (6). 1988, 34-44. 1173. N. Ayache and 0. D. Faugeras, Building, registrating, and fusing noisy visual maps, ZJRR 7 (6). 1988, 45-65. 1174. J. Porrill, Optimal combination and constraints for geometrical sensor data, ZJRR 7 (61, 1988. 66-77.
1175. J. M. Richardson and K. A. Marsh, Fusion of multisensor data, ZJRR 7 (6), 1988, 78-96. 1176. H. F. Durrant-Whyte, Sensor models and multisensor integration, ZJZZR7 (61, 1988, 97-113.
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1177. T. Henderson, E. Weitz, C. Hansen, and A. Mitiche, Multisensor knowledge systems: interpreting 3D structure, ZJRR 7 (61, 1988, 114-137. 1178. S. A. Stansfield, A robotic perceptual system utilizing passive vision and active touch, ZJZtR 7 (6), 1988, 138-161. 1179. Y. Yeshurun and E. L. Schwartz, Shape description with a space-variant sensor: algorithms for scan-path, fusion, and convergence over multiple scans, T-PAMI 11, 1989, 1217-1222. 1180. S. A Hutchinson and A. C. Kak, Planning sensing strategies in a robot work cell with multi-sensor capabilities, T-M 5, 1989, 765-783. 1181. R. C. Luo and M. G. Kay, Multisensor integration and fusion in intelligent systems, T-SMC 19, 1989,901-931. 1182. C. Brown, Gaze controls with interactions and delays, IUW, 200-218. 1183. K. Ikeuchi and J. C. Robert, Modeling sensor detectability with VANTAGE geometric/sensor modeler, IUW, 721-746. 1184. K. Tarabanis and R. Y. Tsai, Viewpoint planning: the visibility constraint, IUW, 893-903. 1185. T. S. Levitt and D. T. Lawton, Visual re-acquisition of geographic locations, IUW, 950-956. 1186. D. H. Graf and W. R. LaLonde, Neuroplanners and their application to eyes/head/neck coordination, IJCAI, 1022-1028. 1187. D. H. Ballard, Reference frames for animate vision, IJCAI, 1635-1641.