• DocumentCode
    3429291
  • Title

    An effective and fast soccer ball detection and tracking method

  • Author

    Tong, Xiao-Feng ; Lu, Han-Qing ; Liu, Qing-Shan

  • Author_Institution
    Nat. Lab. of Pattern Recognition, Chinese Acad. of Sci., Beijing, China
  • Volume
    4
  • fYear
    2004
  • fDate
    23-26 Aug. 2004
  • Firstpage
    795
  • Abstract
    A ball detection and tracking approach in real soccer game is proposed in this paper. In view of difficulties of direct detection, an indirect strategy based on non-ball elimination is applied. We distinguish the ball with a coarse-to-fine process. Game field is firstly extracted and the posterior operations are restricted within it. Then, at the coarse step, some distinct non-ball regions are removed via evaluation of color and shape. And at the fine step, the remained regions are further examined and the optimal one is determined as ball. Afterwards. CONDENSATION algorithm is utilized to track ball. Region optimization is appended to adapt to the ball´s size and color/texture changes in response to movement along sequential frames through maximizing the normalization sum of intensity gradient around its perimeter. Moreover, a confidence measure representing the ball region´s reliability is presented to guide possible re-detection for continuous tracking. Experiments have demonstrated the method is valid and fast in real soccer sequences.
  • Keywords
    image colour analysis; image sequences; optimisation; tracking; CONDENSATION algorithm; coarse-to-fine process; color evaluation; fast soccer ball detection; nonball elimination; real soccer sequence; region optimization; sequential frames; shape evaluation; tracking method; Automation; Change detection algorithms; Event detection; Games; Image sequences; Laboratories; Object detection; Pattern recognition; Robustness; Shape;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on
  • ISSN
    1051-4651
  • Print_ISBN
    0-7695-2128-2
  • Type

    conf

  • DOI
    10.1109/ICPR.2004.1333892
  • Filename
    1333892