Image Region Selection and Ensemble for Face Recognition

In this paper, a novel framework for face recognition, namely Selective Ensemble of Image Regions (SEIR), is proposed. In this framework, all possible regions in the face image are regarded as a certain kind of features. There are two main steps in SEIR: the first step is to automatically select several regions from all possible candidates; the second step is to construct classifier ensemble from the selected regions. An implementation of SEIR based on multiple eigenspaces, namely SEME, is also proposed in this paper. SEME is analyzed and compared with eigenface, PCA + LDA, eigenfeature, and eigenface + eigenfeature through experiments. The experimental results show that SEME achieves the best performance.