Shadow Graphs and Surface Reconstruction

We present a method to solve shape-from-shadow using shadow graphs which give a new graph-based representation for shadow constraints. It can be shown that the shadow graph alone is enough to solve the shape-from-shadow problem from a dense set of images. Shadow graphs provide a simpler and more systematic approach to represent and integrate shadow constraints from multiple images. To recover shape from a sparse set of images, we propose a method for integrated shadow and shading constraints. Previous shape-from-shadow algorithms do not consider shading constraints while shapefrom-shading usually assumes there is no shadow. Our method is based on collecting a set of images from a fixed viewpoint as a known light source changes its position. It first builds a shadow graph from shadow constraints from which an upper bound for each pixel can be derived if the height values of a small number of pixels are initialized properly. Finally, a constrained optimization procedure is designed to make the results from shape-from-shading consistent with the upper bounds derived from the shadow constraints. Our technique is demonstrated on both synthetic and real imagery.