关键词: 目标跟踪, 局部遮挡, 团块, Mean-Shift算法

Abstract: Traditional Mean-Shift based object tracking adopts whole features for tracking，and is hard to track well under object occlusion.A new local feture based method is proposed，which combines the blob modeling and mean-shift together.Firstly，the blob modeling for the tracked object is built，and then each blob is tracked by the Mean-Shift method.Finally the new position of object is determined.The proposed method can select unoccluded blob for object tracking when occlusion occurs.The background-weighted Mean-Shift method is adopted to improve the robustness to the background disturbance.Experimental results show that the method can track the object exactly under the circumstance of partial occlusion，and the performance is better than that of traditional Mean-Shift based method.

Key words: object tracking, partial occlusion, blob, Mean-Shift algorithm