Sensitivity to variations in pose is a challenging problem in face recognition using appearance-based methods. More specifically, the appearance of a face changes dramatically when viewing and/or lighting directions change. Various approaches have been proposed to solve this difficult problem. They can be broadly divided into three classes: 1) multiple image based methods where multiple images of various poses per person are available, 2) hybrid methods where multiple example images are available during learning but only one database image per person is available during recognition, and 3) single image based methods where no example based learning is carried out. In this paper, we present a method that comes under class 3. This method based on shape-from-shading (SFS) improves the performance of a face recognition system in handling variations due to pose and illumination via image synthesis.
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