ShadowCuts: Photometric Stereo with Shadows

We present an algorithm for performing Lambertian photometric stereo in the presence of shadows. The algorithm has three novel features. First, a fast graph cuts based method is used to estimate per pixel light source visibility. Second, it allows images to be acquired with multiple illuminants, and there can be fewer images than light sources. This leads to better surface coverage and improves the reconstruction accuracy by enhancing the signal to noise ratio and the condition number of the light source matrix. The ability to use fewer images than light sources means that the imaging effort grows sublinearly with the number of light sources. Finally, the recovered shadow maps are combined with shading information to perform constrained surface normal integration. This reduces the low frequency bias inherent to the normal integration process and ensures that the recovered surface is consistent with the shadowing configuration The algorithm works with as few as four light sources and four images. We report results for light source visibility detection and high quality surface reconstructions for synthetic and real datasets.