Tracking method for object of partial occlusion based on combination of blob modeling and Mean-Shift
Juan Liu · Computer Engineering and Applications Journal · 2011
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.Experimen- tal 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.