• DocumentCode
    2462143
  • Title

    The 3D-3D Registration Problem Revisited

  • Author

    Li, Hongdong ; Hartley, Richard

  • Author_Institution
    Australian Nat. Univ., Canberra
  • fYear
    2007
  • fDate
    14-21 Oct. 2007
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    We describe a new framework for globally solving the 3D-3D registration problem with unknown point correspondences. This problem is significant as it is frequently encountered in many applications. Existing methods are not fully satisfactory, mainly due to the risk of local minima. Our framework is grounded on the Lipschitz global optimization theory. It achieves a guaranteed global optimality without any initialization. By exploiting the special structure of the problem itself and of the 3D rotation space SO(3), we propose a box-and-ball algorithm, which solves the problem efficiently. The main idea of the work can be applied to many other problems as well.
  • Keywords
    computer vision; image registration; octrees; optimisation; 3D rotation space; 3D-3D registration problem; Lipschitz global optimization theory; computer vision; local minima risk; octree box-and-ball algorithm; Application software; Australia; Biomedical imaging; Computer vision; Graphics; Iterative algorithms; Iterative closest point algorithm; Medical robotics; Object recognition; Principal component analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision, 2007. ICCV 2007. IEEE 11th International Conference on
  • Conference_Location
    Rio de Janeiro
  • ISSN
    1550-5499
  • Print_ISBN
    978-1-4244-1630-1
  • Electronic_ISBN
    1550-5499
  • Type

    conf

  • DOI
    10.1109/ICCV.2007.4409077
  • Filename
    4409077