• DocumentCode
    3431907
  • Title

    Robust background subtraction and maintenance

  • Author

    Zang, Qi ; Klette, Reinhard

  • Author_Institution
    CITR Tamaki, Auckland Univ., New Zealand
  • Volume
    2
  • fYear
    2004
  • fDate
    23-26 Aug. 2004
  • Firstpage
    90
  • Abstract
    Background subtraction is one of the main techniques to extract moving objects from background scenes. A mixture of Gaussians is a common model for background subtraction that has been used in many applications. However modelling background pixels using this model results into a low-level process at pixel level. Some of its main drawbacks are: a subtracted (moving object) region may contain holes; it cannot solve partial occlusion problems, and it requires updates in cases of shadows or sudden changes in the scene. We present a multi-layered mixture of Gaussians model named PixelMap. We combine the mixture of Gaussians model with concepts defined by region level and frame level considerations. Our experimental results show that our method improved the accuracy of extracting moving objects from background. A single stationary camera has been used.
  • Keywords
    Gaussian processes; feature extraction; image motion analysis; Gaussian mixture; object extraction; robust background subtraction; stationary camera; Bayesian methods; Cameras; Colored noise; Differential equations; Gaussian processes; Image segmentation; Layout; Monitoring; Robust stability; Robustness;
  • 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.2004.1334047
  • Filename
    1334047