Mean-Shift Algorithm Fusing Multi Feature
The mean shift algorithm(Mean Shift,MS)has been widely used because of the advantages of fewer iteration times and better real-time performance.In the other hand,because of the use of single color histogram representation of the target feature,the MS algorithm cant always track well in complex condition.Aiming at the problem that the traditional Mean-Shift algorithm is unstable when the background color is similar to the target color or there is partial occlusion.In this paper,the original color features in traditional mean shift algorithm is transformed into HSV color feature and the textural feature is integrated into it to improve the tracking performance in the case of the background color is similar to the target color,and the four neighborhood search method(4 areas with the same size are expanded around the candidate area)is applied to solve the problem of partial occlusion.The comparisons of experiments show that the algorithm of this paper has higher accuracy than the traditional MS algorithm and the background weighted MS algorithm in the above complex environment,besides,the proposed algorithm has a good operating efficiency.
target tracking color feature texture feature mean-shift
Xian Zhong Kun Tu Hongxia Xia
School of Science,Wuhan University of Technology Hubei Province,Wuhan,China
国际会议
重庆
英文
1245-1249
2017-03-25（万方平台首次上网日期，不代表论文的发表时间）