基于改进的均值漂移算法的目标跟踪

提出了一种基于目标颜色特征的改进的均值漂移算法，对符合颜色模板的目标点不论其在直方图中的概率大小，都赋予相同的最大权值，使目标最大限度地成为密度极值区，以克服干扰影响，并提出了一种分块检测遮挡算法，遮挡期间不更新颜色模板，以保证遮挡后恢复准确的跟踪。实验结果表明该算法具有较强的鲁棒性，能有效实现复杂场景下的目标跟踪。

Target Tracking Based on Improved Mean Shift Algorithm

An improved mean shift algorithm is proposed based on color feature. The target point which accords with the color template has the largest weight regardless of its probability in the histogram, making the target density peak and overcoming the serious clutter and occlusion. Effective occlusion detection method based on sub-block is put forward and the color template isn’t updated to resume the accurate tracking after occlusion. Experimental results indicate it is robust and has good performances under complex background.