Photometric stereo under unknown light sources using robust SVD with missing data

In this paper, we propose a novel photometric stereo method that uses singular value decomposition. Singular value decomposition can solve the photometric stereo problem when the light source direction is unknown; however, it has the critical problem of being sensitive to outliers. We therefore propose a novel singular value decomposition method that is robust to outliers. We also show some results of our photometric stereo method when applied to objects that involve not only diffuse reflection but also specular reflection.