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A Moving Object Tracking Method Based on Mean Shift Rectification

机译:基于均值漂移校正的运动目标跟踪方法

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The traditional mean shift tracking method can not acquire high accuracy when the object undergoes partial occlusion. An improved tracking method called mean shift rectification is proposed. The candidate matching points in target region searched by mean shift method are filtered using a loglikelihood ratio function, and the target region is divided into subregions. Then the spatial matching restrictions are considered to compute the difference displacement through partial histogram matching. Finally all the difference displacements between reference subregions and target subregions are syncretized to compute the rectification displacement. The experiment results show the improvements of the proposed method in robustness and accuracy.
机译:当物体经历部分遮挡时,传统的均值漂移跟踪方法无法获得很高的精度。提出了一种改进的跟踪方法,称为均值漂移校正。使用对数似然比函数对通过均值平移法搜索的目标区域中的候选匹配点进行滤波,然后将目标区域划分为子区域。然后考虑空间匹配限制,以通过部分直方图匹配来计算差异位移。最后,将参考子区域和目标子区域之间的所有差异位移融合在一起,以计算整流位移。实验结果表明,该方法在鲁棒性和准确性上都有改进。

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