Efficient facial feature detection using entropy and svm

Abstract

In this paper, an efficient algorithm for facial feature detection is presented. Complex regions in a face image, such as the eye, exhibit unpredictable local intensity and hence high entropy. We use this characteristic to obtain eye candidates, and then these candidates are sent to a SVM classifier to get real eyes. According to the geometry relationship of human face, mouth search region is specified by the coordinates of the left eye and the right eye. And then precise mouth detection is done. Experimental results demonstrate the effectiveness of the proposed method. © Springer-Verlag Berlin Heidelberg 2008.