基于Haar检测和改进的Camshift的人脸跟踪

Face tracking based on Haar detection and improved Camshift algorithm

针对人脸目标的遮挡大角度倾斜和旋转状态下的目标跟踪丢失问题,提出了一种时间回溯的人脸跟踪方法。以Haar特征检测和改进Camshift算法为基础,在Haar分类器中引入时间变量,实现回溯;在概率密度图像中引入变加权直方图模型,加大了人脸区域的权重,并辅以光照补偿、椭圆模板匹配等方法。实验表明,本文算法能够有效克服遮挡问题和丢失问题,效果优于其他算法,并满足实时跟踪的需要。

It has been difficult problem in face tracking and recognition that of the coveraged target face, wide-angle tilt and rotation can cause tracking lost. For above issues, a time rewinding face tracking algo rithm based on Haar feature detection and improved Camshift is proposed. Time variable is introduced in Haar classifiers to realize time backtracking and the change-weighted histogram is added to the probabil ity density image to increase the weight of face region. Supplemented with light compensation and ellipse template matching, the new algorithm effectively overcomes the problem of face coverage and target lost, and is more effective than other algorithms.