The target representation method of a tracked target has great influence on the robustness of the tracking algorithm. In this paper

we introduce a new texture feature called Opponent Color Local Binary Patterns (OCLBP). By analyzing the correlation among different color channels and all the ten texture patterns of the OCLBP

we select the texture histogram of the key points which correspond to only the seven major patterns of the OCLBP to represent the target candidate region.Finally

this model is integrated into the mean shift framework for object tracking. The experimental results illustrate that the proposed major OCLBP patterns based method can significantly improve the performance of Mean Shift object tracking algorithm.