Robust Face Recognition via Occlusion Detection and Masking

Abstract

Sparse representation-based classification (SRC) method has demonstrated promising results in face recognition (FR). In this paper, we consider the problem of face recognition with occlusion. In sparse representation-based classification method, the reconstruction residual of test sample over the training set is usually heterogeneous with the training samples, highlighting the occlusion part in test sample. We detect the occlusion part by extracting a mask from the reconstruction residual through threshold operation. The mask will be applied in the representation-based classification framework to eliminate the impact of occlusion in FR. The method does not assume any prior knowledge about the occlusion, and extensive experiments on publicly available databases show the efficacy of the method.