Face illumination normalization based on illumination-separated face identity texture subspace

Abstract

Robust face recognition under various illumination environments is essential for successful commercialization, but difficult to achieve. For robust face recognition with respect to illumination variations, illumination normalization of face images is usually necessary as a preprocessing step. Most of previously proposed illumination normalization methods cannot handle cast shadows in face images. In this paper, we propose a new face illumination normalization method based on the illumination-separated face identity texture subspace. Since the subspace is constructed so as to be separated from the effects of illumination variations, the projection of face images into the subspace produces a good illumination-normalized face images. Through experiments, it is shown that the proposed face illumination normalization method can effectively eliminate cast shadows as well as attached shadows and achieves good face illumination normalization.