• DocumentCode
    3549194
  • Title

    Energy minimization via graph cuts: settling what is possible

  • Author

    Freedman, Daniel ; Drineas, Petros

  • Author_Institution
    Dept. of Comput. Sci., Rensselaer Polytech. Inst., Troy, NY, USA
  • Volume
    2
  • fYear
    2005
  • fDate
    20-25 June 2005
  • Firstpage
    939
  • Abstract
    The recent explosion of interest in graph cut methods in computer vision naturally spawns the question: what energy functions can be minimized via graph cuts? This question was first attacked by two papers of Kolmogorov and Zabih, in which they dealt with functions with pair-wise and triplewise pixel interactions. In this work, we extend their results in two directions. First, we examine the case of k-wise pixel interactions; the results are derived from a purely algebraic approach. Second, we discuss the applicability of provably approximate algorithms. Both of these developments should help researchers best understand what can and cannot be achieved when designing graph cut based algorithms.
  • Keywords
    computer vision; functions; graph theory; minimisation; approximate algorithm; computer vision; energy function minimization; graph cut method; k-wise pixel interaction; Algorithm design and analysis; Application software; Computer science; Computer vision; Explosions; Minimization methods; NP-complete problem; Polynomials; Stereo vision; Sufficient conditions; energy minimization; graph cuts;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on
  • ISSN
    1063-6919
  • Print_ISBN
    0-7695-2372-2
  • Type

    conf

  • DOI
    10.1109/CVPR.2005.143
  • Filename
    1467543