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MOVING OBJECT DETECTION AND TRACKING BASED ON BACKGROUND SUBTRACTION

LIU Ya\ AI Hai zhou\ XU Guang you (Department of Computer Science and Technology, Tsinghua University)  
An approach to detecting and tracking moving objects with a static camera is presented in this paper. A modified mixture Gaussian model is used as the adaptive background updating method. Foreground objects are segmented based on an improved binary connected component analysis. Kalman filtering is used for object tracking. To deal with the problems of occlusion between objects in tracking, various situations are analyzed and a measure of reliability of moving objects is adopted which makes the tracker more effective. Experiments on several outdoor video streams that show convictive object detection and tracking performance demonstrate its strong adaptability to lighting changes, shadows and occlusions.
【Fund】: 国防预研项目 7B8资助
【CateGory Index】: TP391.4
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