Automatic pedestrian detection and tracking for real-time video surveillance

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.