Face identification from one single sample face image

This paper is addressing a challenging face recognition problem: face identification from one single face image. We present a novel approach to face identification, which is capable to identify a person from face images that are significantly different from the sample image in terms of illumination, camera view angles and expressions. The approach is based on a new measurement of dissimilarity between the two face images. A person is identified based on the smallest dissimilarity, which is the summation of the dissimilarities of all pairs of observations extracted from the face image on both vertical and horizontal directions. Our experiment results tested on both the AR face database and the CMU PIE face database shows that the proposed method outperforms the PCA, LDA, LFA based approaches.