Face relighting for face recognition under generic illumination
The performance of current face recognition systems suffers heavily from variations in lighting. To deal with this problem, this paper presents a novel illumination normalization approach, by relighting faces to a canonical illumination, based on harmonic images. Benefiting from the observation that human faces share similar shape, and the albedo of the face surface is quasi-constant, we first estimate the nine low-frequency components of the lighting from the input face image. Then, the face image is normalized by relighting it to a canonical illumination, based on the illumination ratio image. For face recognition purposes, two kinds of canonical illumination, uniform and frontal point lighting, are considered, between which the former encodes merely texture information, while the latter encodes both texture and shading information. Our experimental results show that the proposed relighting normalization can significantly improve the performance of a face recognition system.