Face Recognition with Image Misalignment via Structure Constraint Coding

Face recognition (FR) via sparse representation has been widely studied in the past several years. Recently many sparse representation based face recognition methods with simultaneous misalignment were proposed and showed interesting results. In this paper, we present a novel method called structure constraint coding (SCC) for face recognition with image misalignment. Unlike those sparse representation based methods, our method does image alignment and image representation via structure constraint based regression simultaneously. Here, we use the nuclear norm as a structure constraint criterion to characterize the error image. Compared with the sparse representation based methods, SCC is more robust for dealing with illumination variations and structural noise (especially block occlusion). Experimental results on public face databases verify the effectiveness of our method.