• DocumentCode
    2714925
  • Title

    Discovering and exploiting 3D symmetries in structure from motion

  • Author

    Cohen, Andrea ; Zach, Christopher ; Sinha, Sudipta N. ; Pollefeys, Marc

  • Author_Institution
    ETH Zurich, Zurich, Switzerland
  • fYear
    2012
  • fDate
    16-21 June 2012
  • Firstpage
    1514
  • Lastpage
    1521
  • Abstract
    Many architectural scenes contain symmetric or repeated structures, which can generate erroneous image correspondences during structure from motion (Sfm) computation. Prior work has shown that the detection and removal of these incorrect matches is crucial for accurate and robust recovery of scene structure. In this paper, we point out that these incorrect matches, in fact, provide strong cues to the existence of symmetries and structural regularities in the unknown 3D structure. We make two key contributions. First, we propose a method to recover various symmetry relations in the structure using geometric and appearance cues. A set of structural constraints derived from the symmetries are imposed within a new constrained bundle adjustment formulation, where symmetry priors are also incorporated. Second, we show that the recovered symmetries enable us to choose a natural coordinate system for the 3D structure where gauge freedom in rotation is held fixed. Furthermore, based on the symmetries, 3D structure completion is also performed. Our approach significantly reduces drift through ”structural” loop closures and improves the accuracy of reconstructions in urban scenes.
  • Keywords
    image matching; image motion analysis; 3D structure completion; 3D symmetry; architectural scene; constrained bundle adjustment formulation; image correspondence; incorrect match detection; incorrect match removal; repeated structure; scene structure; structural regularity; structure from motion computation; symmetric structure; Buildings; Cameras; Feature extraction; Image reconstruction; Mirrors; Periodic structures; Solid modeling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on
  • Conference_Location
    Providence, RI
  • ISSN
    1063-6919
  • Print_ISBN
    978-1-4673-1226-4
  • Electronic_ISBN
    1063-6919
  • Type

    conf

  • DOI
    10.1109/CVPR.2012.6247841
  • Filename
    6247841