An Effective Face Recognition under Illumination and Pose Variations

Illumination and pose variations that occur on face images degrade the performance of face recognition. In this paper, we propose a novel approach for handling illumination and pose variations for face recognition simultaneously. We use the two-dimensional view-based face recognition method and the shadow compensation method to deal with both variations. We construct a subspace for each pose and use the relationship between facial feature points to identify the poses. Since most human faces are similar in shape, we can find the shadow characteristics that the illumination variation makes on a face depending on the direction of light. By using these characteristics, we can compensate for illumination variation in face images. The proposed method is simple and requires much less computational effort than the other methods based on 3D models, and at the same time, provides a comparable recognition rate.