• DocumentCode
    639448
  • Title

    In Defense of 3D-Label Stereo

  • Author

    Olsson, Carl ; Ulen, Johannes ; Boykov, Yuri

  • Author_Institution
    Centre for Math. Sci., Lund Univ., Lund, Sweden
  • fYear
    2013
  • fDate
    23-28 June 2013
  • Firstpage
    1730
  • Lastpage
    1737
  • Abstract
    It is commonly believed that higher order smoothness should be modeled using higher order interactions. For example, 2nd order derivatives for deformable (active) contours are represented by triple cliques. Similarly, the 2nd order regularization methods in stereo predominantly use MRF models with scalar (1D) disparity labels and triple clique interactions. In this paper we advocate a largely overlooked alternative approach to stereo where 2nd order surface smoothness is represented by pairwise interactions with 3D-labels, e.g. tangent planes. This general paradigm has been criticized due to perceived computational complexity of optimization in higher-dimensional label space. Contrary to popular beliefs, we demonstrate that representing 2nd order surface smoothness with 3D labels leads to simpler optimization problems with (nearly) sub modular pairwise interactions. Our theoretical and experimental results demonstrate advantages over state-of-the-art methods for 2nd order smoothness stereo.
  • Keywords
    Markov processes; computational complexity; optimisation; stereo image processing; 1D disparity labels; 3D-label stereo; MRF models; computational complexity; deformable contours; higher order interactions; higher order smoothness; higher-dimensional label space; optimization problems; pairwise interactions; scalar disparity labels; second order regularization methods; second order smoothness stereo; second order surface smoothness; submodular pairwise interactions; triple clique interactions; Cameras; Computational modeling; Optimization; Proposals; Stereo vision; Surface reconstruction; Three-dimensional displays;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition (CVPR), 2013 IEEE Conference on
  • Conference_Location
    Portland, OR
  • ISSN
    1063-6919
  • Type

    conf

  • DOI
    10.1109/CVPR.2013.226
  • Filename
    6619070