People orientation recognition by mixtures of wrapped distributions on random trees
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part V
Qualitative pose estimation by discriminative deformable part models
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part II
People reidentification in surveillance and forensics: A survey
ACM Computing Surveys (CSUR)
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In surveillance videos, cues such as head or body pose provide important information for analyzing people's behavior and interactions. In this paper we propose an approach that jointly estimates body location and body pose in monocular surveillance video. Our approach is based on tracks derived by multi-object tracking. First, body pose classification is conducted using sparse representation technique on each frame of the tracks, generating (noisy) observation on body poses. Then, both location and body pose in 3D space are estimated jointly in a particle filtering framework by utilizing a soft coupling of body pose with the movement. The experiments show that the proposed system successfully tracks body position and pose simultaneously in many scenarios. The output of the system can be used to perform further analysis on behaviors and interactions.