目标表示方法对跟踪方法的鲁棒性有着重要影响。将对立色局部二值模式(OCLBP)纹理算子作为研究对象引入目标表示。通过分析不同颜色通道之间的相关性和OCLBP的10种纹理模式的表征能力,选择目标候选区域中具有OCLBP的7种主要模式的关键点的纹理直方图作为目标模型。最后将该目标表示方法嵌入到Mean Shift框架中,进行目标跟踪。实验结果表明,提出的基于OCLBP主要模式的目标表示方法显著提高了Mean Shift目标跟踪方法的性能。

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.