一种结合AdaBoost与mean shift的人眼检测方法

Eye detection is an important part of the face recognition system. It plays a pivotal role in the accuracy of face recognition. In the system, eye detection is divided into coarse detection and fine detection. The haar feature, the AdaBoost algorithm and the attentional cascade are used in the coarse detection to get plenty of candidates. The mean shift, including scale factor, are used in the fine detection to find the maximum position of probability density, which is considered as the ultimate eye position. The experiments show that the algorithm can localize precise eyes for frontal faces in real time.