| Literature DB >> 22516648 |
Aydin Varol1, Appu Shaji, Mathieu Salzmann, Pascal Fua.
Abstract
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.Year: 2012 PMID: 22516648 DOI: 10.1109/TPAMI.2011.196
Source DB: PubMed Journal: IEEE Trans Pattern Anal Mach Intell ISSN: 0098-5589 Impact factor: 6.226