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Green Image
Issue No. 06 - June (2012 vol. 34)
ISSN: 0162-8828
pp: 1118-1130
M. Salzmann , NICTA, Canberra, ACT, Australia
A. Shaji , EPFL-IC-Comput. Vision Lab., Lausanne, Switzerland
A. Varol , EPFL-IC-Comput. Vision Lab., Lausanne, Switzerland
P. Fua , EPFL-IC-Comput. Vision Lab., Lausanne, Switzerland
Most recent approaches to monocular nonrigid 3D shape recovery rely on exploiting point correspondences and work best when the whole surface is well textured. The alternative is to rely on either 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. 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.
surface texture, image texture, solid modelling, surface reconstruction, complex lighting, monocular 3D reconstruction, locally textured surfaces, monocular nonrigid 3D shape recovery, shading information, monocular deformable shape recovery, local surface patches, Shape, Three dimensional displays, Surface reconstruction, Surface texture, Lighting, Training, Image reconstruction, shape from shading., Deformable surfaces, shape recovery

M. Salzmann, A. Shaji, A. Varol and P. Fua, "Monocular 3D Reconstruction of Locally Textured Surfaces," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 34, no. , pp. 1118-1130, 2012.
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