关键词: Kalman滤波器, 信息量度量, Mean-Shift算法, 面积的变化比例

Abstract: The traditional Mean-Shift tracking algorithm of the fixed window-size cannot be adapted to real-time goal of the changes in size. Multi-scale space theory was combined with Kalman filter. First, Kalman filter was introduced to predict the proportion of the target image area, and then this proportion was revised by the observation, which was the proportion of the information of the two adjacent target images using the measurement of the target amount of information in the multscale space theory. Finally, it was implemented by the combination of the Mean-Shift tracking algorithm and Kalman filter to track targets. The improved algorithm can select the proper size of the tracking window in the scenarios that not only of increasing scale but of decreasing scale by the experimental results.

Key words: Kalman filter, the amount of information measure, Mean-Shift algorithm, proportion of the target image area