• DocumentCode
    2542172
  • Title

    Bidirectional tracking using trajectory segment analysis

  • Author

    Sun, Jian ; Zhang, Weiwei ; Tang, Xiaoou ; Shum, Heung-Yeung

  • Author_Institution
    Microsoft Res. Asia, Beijing, China
  • Volume
    1
  • fYear
    2005
  • fDate
    17-21 Oct. 2005
  • Firstpage
    717
  • Abstract
    In this paper, we present a novel approach to keyframe-based tracking, called bi-directional tracking. Given two object templates in the beginning and ending keyframes, the bi-directional tracker outputs the MAP (maximum a posterior) solution of the whole state sequence of the target object in the Bayesian framework. First, a number of 3D trajectory segments of the object are extracted from the input video, using a novel trajectory segment analysis. Second, these disconnected trajectory segments due to occlusion are linked by a number of inferred occlusion segments. Last, the MAP solution is obtained by trajectory optimization in a coarse-to-fine manner. Experimental results show the robustness of our approach with respect to sudden motion, ambiguity, and short and long periods of occlusion.
  • Keywords
    Bayes methods; image motion analysis; image segmentation; image sequences; maximum likelihood estimation; video signal processing; 3D trajectory segment extraction; Bayesian framework; bidirectional tracking; image sequence; keyframe-based tracking; maximum a posterior solution; object templates; occlusion; target object; trajectory segment analysis; Bayesian methods; Bidirectional control; Hidden Markov models; Recursive estimation; Sun; Target tracking; Trajectory; Video compression; Video sequences; Video surveillance;
  • 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.2005.49
  • Filename
    1541324