Precise Face Segmentation for Recognition

In this paper, we present an efficient algorithm for facial component extractions, which are eyes detection and the mouth width measuring, and pose estimation. The algorithm is based on the novel overcomplete wavelet feature template, the support vector machine (SVM) classifier, and the wavelet entropy filtering to robustly detect and segment the T-shape face region. The segmented T-shape face region, which is the smallest area enclosed by the face ellipse including eyes and mouth, is used to select the corresponding view-based classifier for face recognition. The experimental results show that the proposed method is robust against the complex scenes.