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Most recent approaches to monocular non-rigid 3D shape recovery rely on exploiting point correspondences and work best when the whole surface is well-textured. The alternative is to rely either on contours or shading information, which has only been demonstrated in very restrictive settings. Here, we propose a novel approach to monocular deformable shape recovery that can operate under complex lighting and handle partially textured surfaces, whether developable or not. At the heart of our algorithm, are a learned mapping from intensity patterns to the shape of local surface patches and a principled approach to piecing together the resulting local shape estimates. We validate our approach quantitatively and qualitatively using both synthetic and real data.
Karen Scrivener, Paul Bowen, Aslam Kunhi Mohamed, Ziga Casar