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 subblock 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.