• DocumentCode
    383442
  • Title

    Model-based human body tracking

  • Author

    Yu Huang ; Huang, Thomas S.

  • Author_Institution
    Beckman Inst., Illinois Univ., Urbana, IL, USA
  • Volume
    1
  • fYear
    2002
  • fDate
    2002
  • Firstpage
    552
  • Abstract
    Visual tracking of human body movement is a key technology in a number of areas. We present a 2-D model-based method of human body tracking from a monocular video sequence. Morris and Rehg (1998) put forward a 2-D scaled prismatic model for figure registration which has far fewer singularity problems than 3-D models. Here we extend it in a 2-D cardboard human body model with one additional DOF of width change. We set tip a mixture motion model for body movements and then solve body motion parameters using EM in a statistical framework, where the model-based kinematic constraints are incorporated in a linear form. Tracking results from real video sequences are encouraging.
  • Keywords
    image sequences; kinematics; motion estimation; parameter estimation; tracking; 2D cardboard human body model; 2D model-based method; 2D scaled prismatic model; expectation-maximization; figure registration; mixture motion model; model-based human body tracking; monocular video sequence; visual tracking; width change; Application software; Biological system modeling; Cameras; Computer vision; Humans; Kinematics; Parameter estimation; Scanning probe microscopy; Target tracking; Video sequences;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2002. Proceedings. 16th International Conference on
  • ISSN
    1051-4651
  • Print_ISBN
    0-7695-1695-X
  • Type

    conf

  • DOI
    10.1109/ICPR.2002.1044791
  • Filename
    1044791