Automatic pedestrian detection and tracking for real-time video surveillance

Authors:
Hee-Deok Yang;Bong-Kee Sin;Seong-Whan Lee
Affiliations:
Center for Artificial Vision Research, Korea University, Seoul, Korea;Department of Computer Multimedia, Pukyong National University, Pusan, Korea;Center for Artificial Vision Research, Korea University, Seoul, Korea
Venue:
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
Year:
2003

Citing 4
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Abstract

This paper presents a method for tracking and identifying pedestrians from video images taken by a fixed camera at an entrance. A pedestrian may be totally or partially occluded in a scene for some period of time. The proposed approach uses the appearance model for the identification of pedestrians and the weighted temporal texture features. We compared the proposed method with other related methods using color and shape features, and analyzed the features' stability. Experimental results with various real video data revealed that real time pedestrian tracking and recognition is possible with increased stability over 5-15% even under occasional occlusions in video surveillance applications.