Automatic surveillance analyzer using trajectory and body-based modeling

With the continuous improvements in computer-vision techniques, automatic low-cost video surveillance gradually emerges for consumer applications. Successful trajectory estimation and human-body modeling facilitate the semantic analysis of human activities in video sequences. We propose a fast analy...

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Bibliographic Details
Published in:2009 Digest of Technical Papers International Conference on Consumer Electronics 2009-01, p.1-2
Main Authors: Weilun Lao, Jungong Han, de With, P.H.N.
Format: Article
Language:eng ; jpn
Subjects:
Biological system modeling
Gaussian distribution
Humans
Layout
Motion detection
Pixel
Shape
Surveillance
Trajectory
Video sequences
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Summary:With the continuous improvements in computer-vision techniques, automatic low-cost video surveillance gradually emerges for consumer applications. Successful trajectory estimation and human-body modeling facilitate the semantic analysis of human activities in video sequences. We propose a fast analyzer for surveillance video, which aims at automatic analysis of human behavior and semantic events. Our analyzer employs visual cues to track moving persons and classify human-body postures from a monocular video. It consists of three processing steps: (1) multi-person detection, (2) persons tracking with trajectory estimation, and (3) posture classification. We show attractive experimental results, highlighting the system efficiency and classification capability.
ISSN:2158-3994
2158-4001
DOI:10.1109/ICCE.2009.5012362