关键词: 目标跟踪, Mean Shift, 快速鲁棒特征（SURF）, 分块颜色直方图, Bhattacharyya系数

Abstract: Traditional color histogram Mean Shift（MS） algorithm only considers object’s color statistical information, and ignores object’s space information, so when the object color is close to the background color, or the object’s illumination changes, the traditional MS algorithm easily causes object’s tracking inaccurately or lost. Aiming at this issue, a new tracking algorithm which fuses improved MS and SURF is proposed. The improved MS algorithm gets the preliminary tracking results, which determines block method by the size of the lastest enclosing rectangle and determines their weight coefficient by the Bhattacharyya coefficient of each block. After obtaining the tracking result with MS, this algorithm utilizes SURF to refine it. This algorithm uses linear weighted method to fuse the improved MS’s tracking results and SURF’s. Experimental results show that the new method which fuses improved MS and SURF is better than the traditional MS algorithm and fixed block MS algorithm in tracking performance.

Key words: object tracking, Mean Shift, Speeded Up Robust Feature（SURF）, block color histogram, Bhattacharyya coefficient