• DocumentCode
    3430998
  • Title

    Improved adaptive Gaussian mixture model for background subtraction

  • Author

    Zivkovic, Zoran

  • Author_Institution
    Intelligent & Autonomous Syst. Group, Amsterdam Univ., Netherlands
  • Volume
    2
  • fYear
    2004
  • fDate
    23-26 Aug. 2004
  • Firstpage
    28
  • Abstract
    Background subtraction is a common computer vision task. We analyze the usual pixel-level approach. We develop an efficient adaptive algorithm using Gaussian mixture probability density. Recursive equations are used to constantly update the parameters and but also to simultaneously select the appropriate number of components for each pixel.
  • Keywords
    Gaussian processes; computer vision; recursive functions; adaptive Gaussian mixture model; background subtraction; computer vision; pixel-level approach; probability density; recursive equations; Adaptive algorithm; Cameras; Computer vision; Density functional theory; Equations; Intelligent systems; Layout; Object detection; Pixel; Surveillance;
  • 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.2004.1333992
  • Filename
    1333992
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3430998