MULTIPLE HUMAN DETECTION AND TRACKING BASED ON WEIGHTED TEMPORAL TEXTURE FEATURES
International journal of pattern recognition and artificial intelligence
In this paper, we present a method of tracking and identifying persons in video images taken by a fixed camera situated at an entrance. In video sequences a person 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 persons and the weighted temporal texture features. The weight is related to the size, duration as well as the number of persons adjacent to the target person. Most systems have built an
... ems have built an appearance model for each person to solve occlusion problems. The appearance model contains certain information on the target person. We have 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 sequences revealed that real time person tracking and recognition is possible with increased stability in video surveillance applications even under situations of occasional occlusion. tracking multiple people or part of their bodies. Darrell et al. 3 used disparity and color information to extract and track individual persons. More recently, there has been increasing interest in integrating the temporal information contained in a tracking system. 1 Among the systems listed above, W4 5 system already employs temporal information to improve the performance of tracking and identification. With temporal information, the search range can be narrowed down significantly. In general, tracking people consists of two subtasks, viz. target detection and verification.