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 gener-ated .Experimental results demonstrate that ,the proposed algorithm can track target accurately in the cases of partial occlusion and scale change .%针对视觉跟踪中常见的目标部分遮挡和尺度变化问题，提出了一种基于拓扑约束的多核跟踪算法。首先，提取满足空间分布的位于目标与背景所在边界的Harris角点作为多核跟踪器的中心，然后，采用拓扑约束对多个跟踪结果进行优化，选取跟踪性能好的核跟踪器，构造仿射变换模型，进而得到最终跟踪结果和目标尺度变化信息。实验结果表明，本文算法能对目标进行准确跟踪，并能有效地处理目标的部分遮挡和尺度变化问题。
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