具有自适应MB-LBP前置滤波的CAMShift人脸跟踪算法

CAMShift face tracking with adaptive MB-LBP pre-filter

基于颜色分布的连续自适应均值移动(CAMShift)人脸跟踪算法简单、易于实现,被广泛应用于实时跟踪。但因其采用肤色模型作为跟踪模式,所以当目标处于类肤色背景区域时,跟踪窗口极易错误收敛到背景区域从而导致跟踪失败。为此,本文提出一种具有自适应MB-LBP前置滤波的CAMShift跟踪算法。首先训练一个能检测人脸基本特征的级联MB-LBP节点分类器。当跟踪窗口进入类肤色干扰区时,系统自适应地把该分类器接入作为CAMShift跟踪算法的前置滤波器,以排除背景中的类肤色干扰,提高算法的鲁棒性。实验结果表明,该算法既能有效排除背景中的类肤色干扰、显著提高CAMShift人脸跟踪算法的鲁棒性,又能保持人脸跟踪的实时性。

Since the color probability distribution based continuous adaptive mean shift （CAMShift） face tracking algorithm is simple and easy to be implemented,it is widely used in real-time tracking applications.However,because the CAMShift takes skin color histogram as the tracking model,its tracking is easy to fail when the target appears in a skin-color-like background region.For that,a CAMShift face tracking algorithm using adaptive Multi-Block Local Binary Pattern （MB-LBP） pre-filter is proposed in this paper.Firstly,a MB-LBP cascade classifier,which can well detect the basic characteristics of the face,is trained.If the tracking window enters a skin-color like background region,this pre-filter is then adaptively inserted to eliminate the skin-like-color background interferences.Consequently,the robustness of the tracking algorithm is improved.Experimental results have proved the superior tracking ability of the proposed algorithm under skincolor-like background interferences.