• DocumentCode
    443178
  • Title

    Fixed point probability field for complex occlusion handling

  • Author

    Fleuret, Françcois ; Lengagne, Richard ; Fua, Pascal

  • Author_Institution
    Ecole Polytechnique Federale de Lausanne, Switzerland
  • Volume
    1
  • fYear
    2005
  • fDate
    17-21 Oct. 2005
  • Firstpage
    694
  • Abstract
    In this paper, we show that in a multi-camera context, we can effectively handle occlusions in real-time at each frame independently, even when the only available data comes from the binary output of a simple blob detector, and the number of present individuals is a priori unknown. We start from occupancy probability estimates in a top view and rely on a generative model to yield probability images to be compared with the actual input images. We then refine the estimates so that the probability images match the binary input images as well as possible. We demonstrate the quality of our results on several sequences involving complex occlusions.
  • Keywords
    hidden feature removal; image processing; real-time systems; actual input image; binary input image; blob detector; complex occlusion handling; fixed point probability; multicamera system; multiview multipeople detection; occupancy probability estimation; probability image; real-time system; Bayesian methods; Cameras; Computer vision; Detectors; Hidden Markov models; Image segmentation; Impedance matching; Probability distribution; Robustness; Yield estimation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision, 2005. ICCV 2005. Tenth IEEE International Conference on
  • ISSN
    1550-5499
  • Print_ISBN
    0-7695-2334-X
  • Type

    conf

  • DOI
    10.1109/ICCV.2005.102
  • Filename
    1541321