• DocumentCode
    3410150
  • Title

    Convex shape decomposition

  • Author

    Liu, Hairong ; Liu, Wenyu ; Latecki, Longin Jan

  • Author_Institution
    Huazhong Univ. of Sci. & Technol., Huazhong, China
  • fYear
    2010
  • fDate
    13-18 June 2010
  • Firstpage
    97
  • Lastpage
    104
  • Abstract
    In this paper, we propose a new shape decomposition method, called convex shape decomposition. We formalize the convex decomposition problem as an integer linear programming problem, and obtain approximate optimal solution by minimizing the total cost of decomposition under some concavity constraints. Our method is based on Morse theory and combines information from multiple Morse functions. The obtained decomposition provides a compact representation, both geometrical and topological, of original object. Our experiments show that such representation is very useful in many applications.
  • Keywords
    approximation theory; image segmentation; integer programming; linear programming; shape recognition; Morse theory; concavity constraints; convex shape decomposition; image segmentation; integer linear programming problem; Cost function; Data mining; Image edge detection; Image processing; Image segmentation; Integer linear programming; Motion detection; Q measurement; Shape; Topology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on
  • Conference_Location
    San Francisco, CA
  • ISSN
    1063-6919
  • Print_ISBN
    978-1-4244-6984-0
  • Type

    conf

  • DOI
    10.1109/CVPR.2010.5540225
  • Filename
    5540225