• DocumentCode
    3208606
  • Title

    Tracking multiple humans in crowded environment

  • Author

    Zhao, Tao ; Nevatia, Ram

  • Author_Institution
    Sarnoff Corp., Princeton, NJ, USA
  • Volume
    2
  • fYear
    2004
  • fDate
    27 June-2 July 2004
  • Abstract
    Tracking of humans in dynamic scenes has been an important topic of research. Most techniques, however, are limited to situations where humans appear isolated and occlusion is small. Typical methods rely on appearance models that must be acquired when the humans enter the scene and are not occluded. We present a method that can track humans in crowded environments, with significant and persistent occlusion by making use of human shape models in addition to camera models, the assumption that humans walk on a plane and acquired appearance models. Experimental results and a quantitative evaluation are included.
  • Keywords
    Bayes methods; hidden feature removal; image sequences; object detection; target tracking; video cameras; Bayesian inference; camera models; crowded environment; human shape models; multiple human tracking; occlusion; video sequences; Cameras; Contracts; Government; Humans; Iris; Layout; Motion detection; Research and development; Shape; Video sequences;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition, 2004. CVPR 2004. Proceedings of the 2004 IEEE Computer Society Conference on
  • ISSN
    1063-6919
  • Print_ISBN
    0-7695-2158-4
  • Type

    conf

  • DOI
    10.1109/CVPR.2004.1315192
  • Filename
    1315192