Mean-Shift moving target tracking algorithm based on weighted sub-block

To reduce the tracking errors caused by the background change and occlusion in dynamic scenes, a novel Mean-Shift moving target tracking algorithm based on weighted sub-block is proposed in this paper. Moving target tracking is completed by blocking the target region. The weight of each sub-block is determined by the combination of the similarity between target sub-block and candidate sub-block and the ratio of the target sub-block area and the overall area. At the same time, the edge position of the target sub-block is found by means of a Sobel operator edge detection algorithm. By which, the target sub-block area is obtained. Both of the target region´s RGB color information and the pixel´s position information are taken into consideration while describing the characteristic model of target and candidate region inside each sub-block. The experiments demonstrate that the proposed method is insensitive to the background change and occlusion, and has better tracking performance with higher tracking accuracy and adaptability.