A multi-kernel tracking algorithm based on topology constraint is proposed in the mean-shift framework

in order to overcome problems caused by partial occlusion and scale change in the visual target tracking.Firstly

Harris corners located in the boundary area and satisfying certain space distribution rules are selected as centers of multiple independent kernel-based trackers.Secondly

topology constraint is used to optimize multiple tracking results

and those trackers with better performance are selected to construct the affine transform model between consecutive frames

through which the final tracking result and scale factors are generated.Experimental results demonstrate that

the proposed algorithm can track target accurately in the cases of partial occlusion and scale change.