• DocumentCode
    2329436
  • Title

    Particle Filter Based on Color Feature with Contour Information Adaptively Integrated for Object Tracking

  • Author

    Pu, Bing ; Zhou, Fugen ; Bai, Xiangzhi

  • Author_Institution
    Image Process. Center, Beijing Univ. of Aeronaut. & Astronaut., Beijing, China
  • Volume
    2
  • fYear
    2011
  • fDate
    28-30 Oct. 2011
  • Firstpage
    359
  • Lastpage
    362
  • Abstract
    Particle filter is a probabilistic multi-hypothesis algorithm under the Bayesian framework. In order to establish a robust observing model, in this paper, a novel method which uses a more effective color feature with contour information integrated adaptively is proposed. Experimental results verified that, our approach was efficient.
  • Keywords
    Bayes methods; image colour analysis; object tracking; particle filtering (numerical methods); probability; Bayesian framework; color feature; contour information integrated adaptively; object tracking; particle filter; probabilistic multihypothesis algorithm; robust observing model; Gray-scale; Histograms; Image color analysis; Lighting; Particle filters; Robustness; Shape; adaptive; color feature; contour information; particle filter;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Design (ISCID), 2011 Fourth International Symposium on
  • Conference_Location
    Hangzhou
  • Print_ISBN
    978-1-4577-1085-8
  • Type

    conf

  • DOI
    10.1109/ISCID.2011.192
  • Filename
    6079811
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2329436