DocumentCode :
3559339
Title :
Occlusion Reasoning for Tracking Multiple People
Author :
Hu, Weiming ; Zhou, Xue ; Hu, Min ; Maybank, Steve
Author_Institution :
Inst. of Autom., Chinese Acad. of Sci., Beijing
Volume :
19
Issue :
1
fYear :
2009
Firstpage :
114
Lastpage :
121
Abstract :
Occlusion reasoning is one of the most challenging issues in visual surveillance. In this letter, we propose a new approach for reasoning about occlusions between multiple people. In our approach, occlusion relationships between people are explicitly defined and deduction of the occlusion relationships is integrated into the whole tracking framework. The prior knowledge is supplied by a set of models which include a 2-D elliptical shape model, a spatial-color mixture of Gaussians appearance model, and a motion model with constant velocity. An observation likelihood function is constructed based on the similarity between the observations and the object appearance models with given states. The occlusion relationships are deduced from the current states of the objects and the current observations, using the observation likelihood function. The previous occlusion relationships are not required for deducing the current occlusion relationships. The problem of tracking and occlusion reasoning for more than two people is formulated mathematically, and a solution is proposed based on particle filtering. Experimental results on several real video sequences from indoor and outdoor scenes show the effectiveness of our approach.
Keywords :
Gaussian processes; computer graphics; particle filtering (numerical methods); target tracking; video signal processing; 2D elliptical shape model; Gaussians appearance model; object appearance models; object tracking; observation likelihood function; occlusion reasoning; particle filtering; visual surveillance; Occlusion reasoning; particle filtering; tracking multiple people; visual surveillance;
fLanguage :
English
Journal_Title :
Circuits and Systems for Video Technology, IEEE Transactions on
Publisher :
ieee
Conference_Location :
12/9/2008 12:00:00 AM
ISSN :
1051-8215
Type :
jour
DOI :
10.1109/TCSVT.2008.2009249
Filename :
4703219
Link To Document :
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