• DocumentCode
    2611624
  • Title

    Observation-Switching Linear Dynamic Systems for Tracking Humans Through Unexpected Partial Occlusions by Scene Objects

  • Author

    Peursum, Patrick ; Venkatesh, Svetha ; West, Geoff

  • Author_Institution
    Dept. of Comput., Curtin Univ. of Technol., Perth, WA
  • Volume
    4
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    929
  • Lastpage
    934
  • Abstract
    This paper focuses on the problem of tracking people through occlusions by scene objects. Rather than relying on models of the scene to predict when occlusions will occur as other researchers have done, this paper proposes a linear dynamic system that switches between two alternatives of the position measurement in order to handle occlusions as they occur. The filter automatically switches between a foot-based measure of position (assuming z = 0) to a head-based position measure (given the person´s height) when an occlusion of the person´s lower body occurs. No knowledge of the scene or its occluding objects is used. Unlike similar research (Fleuret et al., 2005; Zhao and Nevatia, 2004), the approach does not assume a fixed height for people and so is able to track humans through occlusions even when they change height during the occlusion. The approach is evaluated on three furnished scenes containing tables, chairs, desks and partitions. Occlusions range from occlusions of legs, occlusions whilst being seated and near-total occlusions where only the person´s head is visible. Results show that the approach provides a significant reduction in false-positive tracks in a multi-camera environment, and more than halves the number of lost tracks in single monocular camera views
  • Keywords
    computer vision; feature extraction; filtering theory; hidden feature removal; target tracking; filtering; foot-based measure; head-based position measure; human tracking; observation-switching linear dynamic systems; occlusion handling; partial occlusions; position measurement; scene objects; Australia; Cameras; Humans; Layout; Measurement standards; Nonlinear filters; Particle filters; Position measurement; Predictive models; Switches;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
  • Conference_Location
    Hong Kong
  • ISSN
    1051-4651
  • Print_ISBN
    0-7695-2521-0
  • Type

    conf

  • DOI
    10.1109/ICPR.2006.888
  • Filename
    1699992