Sparse residue for occluded face image reconstruction and classification

Occlusion problem is one of remaining challenges in face recognition. This work expresses an occluded image as the summation of a non-occluded image and a sparse occlusion. By solving a l1norm minimization problem, we isolate the sparse occlusion from the face image, and simultaneously reconstruct the image. The reconstructed image is same to the original one in most pixels. To classify an occluded image with unknown identity, we first linearly express it using the images of every person, and then make decision based on the residues of the expressions. This paper also presents the relationship between the proposed method and the popular methods. The experiments validate the feasibility of the proposed method.