• DocumentCode
    2461193
  • Title

    Modeling View and Posture Manifolds for Tracking

  • Author

    Lee, Chan-Su ; Elgammal, Ahmed

  • Author_Institution
    Rutgers Univ. Piscataway, Piscataway
  • fYear
    2007
  • fDate
    14-21 Oct. 2007
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    In this paper we consider modeling data lying on multiple continuous manifolds. In particular, we model the shape manifold of a person performing a motion observed from different view points along a view circle at fixed camera height. We introduce a model that ties together the body configuration (kinematics) manifold and the visual manifold (observations) in a way that facilitates tracking the 3D configuration with continuous relative view variability. The model exploits the low dimensionality nature of both the body configuration manifold and the view manifold where each of them are represented separately.
  • Keywords
    image motion analysis; learning (artificial intelligence); pose estimation; tracking; 3D configuration tracking; body configuration manifold; complex motion pose estimation; learning procedure; multiple continuous manifolds; person shape manifold modeling; posture manifolds; visual manifold; Biological system modeling; Cameras; Computer science; Humans; Kinematics; Lighting; Search problems; Shape; Solid modeling; Tracking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision, 2007. ICCV 2007. IEEE 11th International Conference on
  • Conference_Location
    Rio de Janeiro
  • ISSN
    1550-5499
  • Print_ISBN
    978-1-4244-1630-1
  • Electronic_ISBN
    1550-5499
  • Type

    conf

  • DOI
    10.1109/ICCV.2007.4409030
  • Filename
    4409030