Tone-aware sparse representation for face recognition

LingFeng Wang, Huai-Yu Wu, Chunhong Pan

Abstract: It is still a very challenging task to recognize a face in a real world scenario, since the face may be corrupted by many unknown factors. Among them, illumination variation is an important one, which will be mainly discussed in this paper. First, the illumination variations caused by shadow or overexposure are regarded as a multiplicative scaling image over the original face image. The purpose of introducing scaling vector (or scaling image) is to enhance the pixels in shadow regions, while depress the pixels in overexposure regions. Then, based on the scaling vector, we propose a novel tone-aware sparse representation (TASR) model. Finally, a EM-like algorithm is proposed to solve the proposed TASR model. Extensive experiments on the benchmark face databases show that our method is more robust against illumination variations.