Abstract: For improving the performance of the mean shift tracking algorithm based on single color feature,which is adopted to establish the target model when the light changes,a new mean shift object tracking algorithm combining a Kirsch-LBP texture feature with HSV color feature was presented.Firstly,the paper presented a novel adaptive thres-hold Kirsch-LBP feature description operator with light resistance,which uses eight direction difference of the Kirsch operator,uses the LBP template average as an adaptive threshold, and then according to the rotation invariant principle of LBP extracts local texture feature.Secondly,it used the relationship between similarity coefficient of different features as the weighted criteria to construct the new weight.Finally,it was embedded into the mean shift algorithm to realize target tracking.Experimental results show that the algorithm can improve the accuracy of target tracking effectively in the scene of light changing,and improves the performance of traditional mean shift object tracking algorithm.

Key words: Mean shift,Target tracking,Texture feature,Color feature,Weight fusion