Determination of 3D human body postures from a single view

COMPUTER

VISION,

GRAPHICS,

AND IMAGE

PROCESSING

29, 396-398 (1985)

Abstracts of Papers Accepted for Publication PAPERS Topological

Stmctaml

Analysis

of Digitized

Binary

Images

by Border

Following.

SATOSHI

SUZUKI,

Graduate School of Electronic Science and Technology, Shizuoka University, Hamamatsu 432, Japan. KEIICHI ABE, Department of Computer Science, Shizuoka University, Hamamatsu 432, Japan. Received December 16, 1983; revised September 16, 1984; accepted November 13, 1984. Two border following algorithms are proposed for the topological analysis of digitized binary images. The first one determines the surroundness relations among the borders of a binary image. Since the outer borders and the hole borders have a one-to-one correspondence to the connected components of l-pixels and to the holes, respectively, the proposed algorithm yields a representation of a binary image, from which one can extract some sort of features without reconstructing the image. The second algorithm, which is a modified version of the first, follows only the outermost borders (i.e., the outer borders which are not surrounded by holes). These algorithms can be effectively used in component counting, shrinking, and topological structural analysis of binary images, when a sequential digital computer is used.

Determination

of 30

Human

Boa’y Postures

from

P Single

View.

HSI-JIAN

LEE AND

ZEN

CHEN.

The

Institute of Computer Engineering, National Chiao-Ttmg University, Hsinchu, Taiwan, Republic of China. Received February 8, 1984; revised September 24, 1984; accepted November 13, 1984. In this paper a method is proposed to recover and interpret the 3D body structures of a person from a single view, provided that (1) at least six feature points on the head and a set of body joints are available on the image plane, and (2) the geometry of head and lengths of body segments formed by joints are known. First of all, the feature points on the head in the head-centered coordinate system and their image projections are used to determine a transformation matrix. Then, the camera position and orientations are extracted from the matrix. Finally, the 3D coordinates of the head points expressed in the camera-centered coordinate system are obtained. Starting from the coordinates of the neck, which is a head feature point, the 3D coordinates of other joints are determined one by one under the assumption of the fixed lengths of the body segments. A binary interpretation tree is used to represent the 2”-’ possible body structures, if a human body has n joints. To determine the final feasible body structures, physical and motion constraints are used to prune the interpretation tree. Formulas and rules required for the tree pruning are stated. Experiments are used to illustrate the pruning powers of these constraints. In the two cases of input data chosen, a unique or nearly unique solution of the body structure is obtained.

A

Gaassiaa-

Weighted

Mahiresolation

Edge

Detector.

RALPH

Center for Automation Received November 13, 1984.

HARTLEY.

search, University of Maryland, College Park, Maryland 20742.

Re-

A Hueckel-like edge detector is developed which weights the neighborhood of a point according to a Gaussian function. This edge detector is found to be a generalization of both a Gaussian weighted gradient edge detector and of a zero crossing edge detector. A hierarchical structure, called a pyramid, allows a fast implementation of the operator in which versions of the operator with many different neighborhood sixes are applied to an image simultaneously.

“Form-Imwicnt” AND

Mappiag Stmtegy for 20 Shqw Recogaition. L. MASSONE, G. SANDINI, Department of Communication, Computer and System Sciences, Via Opera Pia Genova. Received August 5,1983; revised August 6,1984; accepted November 27, 1984. Top&gical

V. TAGLIASCO.

lla-16145

396 0734-189X/85 Copyright All rights

$3.00

6 1985 by Academic Press. Inc. of reproduction in any form reserved.