Mean-Shift Algorithm with Adaptive Window Based on UKF

doi:10.3969/j.issn.1000-3428.2011.14.052

Abstract

Abstract: The traditional fixed bandwidth Mean-Shift tracking algorithm can not have an effective tracking for any changes in targets. An novel method is proposed that is multi-scale space theory combined with Unscented Kalman Filter(UKF). UKF filter is introduced to predict the information in the tracking window which is calculated by the multi-scale space theory. The proportion of the target image area is got by the modified information. It is implemented by the combination of the Mean-Shift tracking algorithm and UKF to track targets. Experimental result confirms the effectiveness of the improved algorithm.

Key words: object tracking, Unscented Kalman Filter(UKF), Mean-Shift algorithm, information measure

摘要： 传统的Mean-Shift跟踪算法窗口固定，不能对尺度任意变化的目标进行有效跟踪。为此，提出一种多尺度理论与无味卡尔曼滤波器(UKF)相结合的视频跟踪改进算法。利用多尺度理论统计跟踪窗内的信息量，使用UKF对得到的信息量进行预测，通过修正后的信息量计算窗口变化比例系数，对尺度任意变化的目标进行跟踪。实验结果证明，该算法能对尺度任意变换的目标进行有效跟踪。

关键词: 目标跟踪, 无味卡尔曼滤波器, Mean-Shift算法, 信息度量

CLC Number:

TP18

YANG Fan, ZHENG Chun-Gong, YANG Gang. Mean-Shift Algorithm with Adaptive Window Based on UKF[J]. Computer Engineering, 2011, 37(14): 158-160.

杨帆, 郑春红, 杨刚. 基于UKF的窗口自适应Mean-Shift算法[J]. 计算机工程, 2011, 37(14): 158-160.

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