Partial occlusions in face images pose a great problem for most face recognition algorithms. Several solutions to this problem have been proposed over the years – ranging from d...
In this paper, we propose a new method for face recognition under varying illumination conditions using a single input image. Our method is based on a statistical shape-from-shadin...
Abstract. By coding the input testing image as a sparse linear combination of the training samples via l1-norm minimization, sparse representation based classification (SRC) has b...
Face recognition under varying illumination remains a challenging problem. Much progress has been made toward a solution through methods that require multiple gallery images of ea...
In this paper, a discriminative manifold learning method for face recognition is proposed which achieved the discriminative embedding the high dimensional face data into a low dim...