DocumentCode
3208606
Title
Tracking multiple humans in crowded environment
Author
Zhao, Tao ; Nevatia, Ram
Author_Institution
Sarnoff Corp., Princeton, NJ, USA
Volume
2
fYear
2004
fDate
27 June-2 July 2004
Abstract
Tracking of humans in dynamic scenes has been an important topic of research. Most techniques, however, are limited to situations where humans appear isolated and occlusion is small. Typical methods rely on appearance models that must be acquired when the humans enter the scene and are not occluded. We present a method that can track humans in crowded environments, with significant and persistent occlusion by making use of human shape models in addition to camera models, the assumption that humans walk on a plane and acquired appearance models. Experimental results and a quantitative evaluation are included.
Keywords
Bayes methods; hidden feature removal; image sequences; object detection; target tracking; video cameras; Bayesian inference; camera models; crowded environment; human shape models; multiple human tracking; occlusion; video sequences; Cameras; Contracts; Government; Humans; Iris; Layout; Motion detection; Research and development; Shape; Video sequences;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision and Pattern Recognition, 2004. CVPR 2004. Proceedings of the 2004 IEEE Computer Society Conference on
ISSN
1063-6919
Print_ISBN
0-7695-2158-4
Type
conf
DOI
10.1109/CVPR.2004.1315192
Filename
1315192
Link To Document