• DocumentCode
    3016825
  • Title

    P3 & Beyond: Solving Energies with Higher Order Cliques

  • Author

    Kohli, Pushmeet ; Kumar, M. Pawan ; Torr, Philip H S

  • Author_Institution
    Oxford Brookes Univ., Oxford
  • fYear
    2007
  • fDate
    17-22 June 2007
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    In this paper we extend the class of energy functions for which the optimal alpha-expansion and alphabeta-swap moves can be computed in polynomial time. Specifically, we introduce a class of higher order clique potentials and show that the expansion and swap moves for any energy function composed of these potentials can be found by minimizing a submodular function. We also show that for a subset of these potentials, the optimal move can be found by solving an st-mincut problem. We refer to this subset as the P3 Potts model. Our results enable the use of powerful move making algorithms i.e. alpha-expansion and alphabeta-swap for minimization of energy functions involving higher order cliques. Such functions have the capability of modelling the rich statistics of natural scenes and can be used for many applications in computer vision. We demonstrate their use on one such application i.e. the texture based video segmentation problem.
  • Keywords
    computational complexity; computer vision; graph theory; image segmentation; video signal processing; P3 Potts model; alpha-expansion; alphabeta-swap moves; computer vision; energy functions minimization; higher order clique potential; natural scenes; polynomial time; st-mincut problem; video segmentation problem; Application software; Approximation methods; Computer vision; Higher order statistics; Inference algorithms; Labeling; Layout; Minimization methods; Polynomials; Random variables;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition, 2007. CVPR '07. IEEE Conference on
  • Conference_Location
    Minneapolis, MN
  • ISSN
    1063-6919
  • Print_ISBN
    1-4244-1179-3
  • Electronic_ISBN
    1063-6919
  • Type

    conf

  • DOI
    10.1109/CVPR.2007.383204
  • Filename
    4270229