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Automatic Building Extraction from Aerial Images
COMPUTER VISION AND IMAGE UNDERSTANDING
Vol. 72, No. 2, November, pp. 99–100, 1998 ARTICLE NO. IV980731
GUEST EDITORS’ INTRODUCTION Automatic Building Extraction from Aerial Images We are pleased to present this Special Issue on the topic of “Automatic Building Extraction from Aerial Images.” The generation and use of 3-D city models (“Cybercity”) is becoming a task of increasing importance. Buildings are the most important elements of these models. Having accurate 3-D models of man-made objects is important for a variety of applications. These include urban planning, environmental studies, telecommunication, risk assessment, transportation, energy production and consumption, simulation, video games, marketing, mission planning, and change detection. Primary data to support such applications is becoming increasingly available from a variety of platforms and sensors, such as aerial and space optical images, radar images and InSar data, and laser scanning data. However, quick and accurate construction of the required 3-D geospatial databases from this data remains a tedious and expensive process. It is widely recognized that automatic detection and description of buildings would go a long way to making more wide use of available imagery possible. The task of automated building detection and reconstruction is difficult for many reasons. The most common source of data are 2-D images which lack direct 3-D information, though range sensors are also coming into use. Aerial images may differ from each other with respect to scale, spectral range of recording, sensor geometry, image quality, imaging conditions (weather, lighting), etc. Buildings can be rather complex structures with many architectural details. They may be surrounded by other disturbing man-made and natural objects. Occlusion of parts is common and the geometrical resolution may be limited. Therefore the corresponding images are of very complex content and highly unstructured. Solving the problem of building detection and reconstruction under these conditions not only is of great practical importance but also provides an excellent testbed for developing computer vision and image understanding techniques. The six papers in this Special Issue describe different approaches to the problem of fully automated building detection and reconstruction. The input sources vary for the different approaches: One uses only a single intensity image, another two (stereo) images, and several use multiple images. One makes use of color and another uses DSM data from laser scanner or image matching in combination with existing 2-D map data. As the results show, the problem of building detection and reconstruction is likely to be with us for a while. However, the papers indicate that substantial progress is being made and that some of the techniques are almost ready for practical use, under limited conditions. The papers also show that the best results can be achieved by appropriate combination of computer vision and photogrammetric concepts and know-how. The idea of assembling this Special Issue arose in conjunction with the preparation of the second workshop on “Automatic Extraction of Man-Made Objects from Aerial and Space Images,” held at the Centro Stefano Franscini, Monte Verita, Ascona, Switzerland in May 1997. Many of the papers in this issue were first presented at the workshop, but in a much shorter form and largely different in content. While the workshop papers were based on invitation only, these CVIU contributions underwent a rather strict triple reviewing procedure.
99 1077-3142/98 $25.00 c 1998 by Academic Press Copyright ° All rights of reproduction in any form reserved.
100
GUEST EDITORS’ INTRODUCTION
We thank the many reviewers for their time-consuming and competent work and Avi Kak, Editor of CVIU, for allowing us to edit this Special Issue. We hope that the readers will find it enjoyable and useful reading! A. Gruen R. Nevatia Guest Editors
Vol. 72, No. 2, November, pp. 99–100, 1998 ARTICLE NO. IV980731
GUEST EDITORS’ INTRODUCTION Automatic Building Extraction from Aerial Images We are pleased to present this Special Issue on the topic of “Automatic Building Extraction from Aerial Images.” The generation and use of 3-D city models (“Cybercity”) is becoming a task of increasing importance. Buildings are the most important elements of these models. Having accurate 3-D models of man-made objects is important for a variety of applications. These include urban planning, environmental studies, telecommunication, risk assessment, transportation, energy production and consumption, simulation, video games, marketing, mission planning, and change detection. Primary data to support such applications is becoming increasingly available from a variety of platforms and sensors, such as aerial and space optical images, radar images and InSar data, and laser scanning data. However, quick and accurate construction of the required 3-D geospatial databases from this data remains a tedious and expensive process. It is widely recognized that automatic detection and description of buildings would go a long way to making more wide use of available imagery possible. The task of automated building detection and reconstruction is difficult for many reasons. The most common source of data are 2-D images which lack direct 3-D information, though range sensors are also coming into use. Aerial images may differ from each other with respect to scale, spectral range of recording, sensor geometry, image quality, imaging conditions (weather, lighting), etc. Buildings can be rather complex structures with many architectural details. They may be surrounded by other disturbing man-made and natural objects. Occlusion of parts is common and the geometrical resolution may be limited. Therefore the corresponding images are of very complex content and highly unstructured. Solving the problem of building detection and reconstruction under these conditions not only is of great practical importance but also provides an excellent testbed for developing computer vision and image understanding techniques. The six papers in this Special Issue describe different approaches to the problem of fully automated building detection and reconstruction. The input sources vary for the different approaches: One uses only a single intensity image, another two (stereo) images, and several use multiple images. One makes use of color and another uses DSM data from laser scanner or image matching in combination with existing 2-D map data. As the results show, the problem of building detection and reconstruction is likely to be with us for a while. However, the papers indicate that substantial progress is being made and that some of the techniques are almost ready for practical use, under limited conditions. The papers also show that the best results can be achieved by appropriate combination of computer vision and photogrammetric concepts and know-how. The idea of assembling this Special Issue arose in conjunction with the preparation of the second workshop on “Automatic Extraction of Man-Made Objects from Aerial and Space Images,” held at the Centro Stefano Franscini, Monte Verita, Ascona, Switzerland in May 1997. Many of the papers in this issue were first presented at the workshop, but in a much shorter form and largely different in content. While the workshop papers were based on invitation only, these CVIU contributions underwent a rather strict triple reviewing procedure.
99 1077-3142/98 $25.00 c 1998 by Academic Press Copyright ° All rights of reproduction in any form reserved.
100
GUEST EDITORS’ INTRODUCTION
We thank the many reviewers for their time-consuming and competent work and Avi Kak, Editor of CVIU, for allowing us to edit this Special Issue. We hope that the readers will find it enjoyable and useful reading! A. Gruen R. Nevatia Guest Editors