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Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition (1996)
San Francisco, Ca.
June 18, 1996 to June 20, 1996
ISSN: 1063-6919
ISBN: 0-8186-7258-7
pp: 73
D.M. Gavrila , Computer Vision Laboratory, CfAR University of Maryland gavrila,lsd@cfar.umd.edu
L.S. Davis , Computer Vision Laboratory, CfAR University of Maryland gavrila,lsd@cfar.umd.edu
ABSTRACT
We present a vision system for the 3-D model-based tracking of unconstrained human movement. Using image sequences acquired simultaneously from multiple views, we recover the 3-D body pose at each time instant without the use of markers. The pose-recovery problem is formulated as a search problem and entails finding the pose parameters of a graphical human model whose synthesized appearance is most similar to the actual appearance of the real human in the multi-view images. The models used for this purpose are acquired from the images. We use a decomposition approach and a best-first technique to search through the high dimensional pose parameter space. A robust variant of chamfer matching is used as a fast similarity measure between synthesized and real edge images. We present initial tracking results from a large new Humans-In-Action (HIA) database containing more than 2500 frames in each of four orthogonal views. They contain subjects involved in a variety of activities, of various degrees of complexity, ranging from the more simple one-person hand waving to the challenging two-person close interaction in the Argentine Tango.
INDEX TERMS
looking at people, 3-D model-based tracking, human movement, gesture recognition, human-machine interaction
CITATION

L. Davis and D. Gavrila, "3-D model-based tracking of humans in action: a multi-view approach," Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition(CVPR), San Francisco, Ca., 1996, pp. 73.
doi:10.1109/CVPR.1996.517056
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