Journal of Information & Systems Management Wang Xingmei, Dong Hongbin, Chu Yan, Li Lin 5 3 2015 http://www.dline.info/jism/v5n3ed.pdf Mean-shift tracking algorithm is a widely used tool for efficiently tracking target. However, the background change and shade usually lead to tracking errors and low tracking accuracy. In this paper, we introduce a novel Mean-shift tracking algorithm based on weighted sub-block which incorporates the improved level set target extraction. The weight of each sub-block is determined by the similarity of target sub-block and candidate sub-block, also by the ratio of the target sub-block area and the overall area. At the same time, the target sub-block area is found by means of the narrow band level set combined with penalty to improve the extraction accuracy and operating efficiency. Both of the target region’s RGB color information and the pixel’s position information are taken into consideration while describing the feature model of target and candidate region inside each sub-block. Many experimental results demonstrate the successful tracking of targets with background change and shade during the dynamic scene, where the basic Mean-shift tracking algorithm fails. And the proposed method has better tracking performance with higher tracking accuracy and adaptability.