• DocumentCode
    1567391
  • Title

    MRF Modeling for Optical Flow Computation from Multi-Structure Objects

  • Author

    Prinet, V. ; Cassisa, C. ; Tang, F.F.

  • Author_Institution
    Inst. of Autom., Chinese Acad. of Sci., Beijing, China
  • fYear
    2006
  • Firstpage
    1093
  • Lastpage
    1096
  • Abstract
    We propose in this paper a new formulation of the equation of the optical flow enabling to compute global and local motions of multi-structure objects (flowers and petals, trees and leaves). The displacement fields are computed using a Markovian random field (MRF) model. Local and global components of the vector flow are both explicitly retrieved. The minimization of the Gibbs energy is achieved with a down-scaling approach, in which we first analyze the motion of the compact object, the sub-structures movement being retrieved in a second stage. We validate and demonstrate the efficiency of our approach on synthetic and real images for various applications.
  • Keywords
    Markov processes; image motion analysis; image sequences; object detection; Gibbs energy; MRF modeling; Markovian random field; displacement field; down-scaling approach; multistructure object motion; optical flow computation; Animation; Automation; Birds; Computer science; Equations; Feathers; Image motion analysis; Optical computing; Pattern recognition; Pixel; Image motion analysis; stochastic fields;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing, 2006 IEEE International Conference on
  • Conference_Location
    Atlanta, GA
  • ISSN
    1522-4880
  • Print_ISBN
    1-4244-0480-0
  • Type

    conf

  • DOI
    10.1109/ICIP.2006.312746
  • Filename
    4106724