• DocumentCode
    1632056
  • Title

    Spatial mixture of Gaussians for dynamic background modelling

  • Author

    Varadarajan, Srenivas ; Miller, Paul ; Huiyu Zhou

  • fYear
    2013
  • Firstpage
    63
  • Lastpage
    68
  • Abstract
    Modelling pixels using mixture of Gaussian distributions is a popular approach for removing background in video sequences. This approach works well for static backgrounds because the pixels are assumed to be independent of each other. However, when the background is dynamic, this is not very effective. In this paper, we propose a generalisation of the algorithm where the spatial relationship between pixels is taken into account. In essence, we model regions as mixture distributions rather than individual pixels. Using experimental verification on various video sequences, we show that our method is able to model and subtract backgrounds effectively in scenes with complex dynamic textures.
  • Keywords
    Gaussian processes; image sequences; image texture; video signal processing; Gaussian distributions; Gaussian spatial mixture; algorithm generalisation; background removal; complex dynamic textures; dynamic background modelling; mixture distributions; pixel modelling; static backgrounds; video sequences; Adaptation models; Approximation algorithms; Clustering algorithms; Dynamics; Equations; Heuristic algorithms; Mathematical model;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Video and Signal Based Surveillance (AVSS), 2013 10th IEEE International Conference on
  • Conference_Location
    Krakow
  • Type

    conf

  • DOI
    10.1109/AVSS.2013.6636617
  • Filename
    6636617