• DocumentCode
    2907092
  • Title

    Fuzzy integral for moving object detection

  • Author

    El Baf, Fida ; Bouwmans, Thierry ; Vachon, Bertrand

  • Author_Institution
    Lab. of Math., La Rochelle Univ., La Rochelle
  • fYear
    2008
  • fDate
    1-6 June 2008
  • Firstpage
    1729
  • Lastpage
    1736
  • Abstract
    Detection of moving objects is the first step in many applications using video sequences like video-surveillance, optical motion capture and multimedia application. The process mainly used is the background subtraction which one key step is the foreground detection. The goal is to classify pixels of the current image as foreground or background. Some critical situations as shadows, illumination variations can occur in the scene and generate a false classification of image pixels. To deal with the uncertainty in the classification issue, we propose to use the Choquet integral as aggregation operator. Experiments on different data sets in video surveillance have shown a robustness of the proposed method against some critical situations when fusing color and texture features. Different color spaces have been tested to improve the insensitivity of the detection to the illumination changes. Then, the algorithm has been compared with another fuzzy approach based on the Sugeno integral and has proved its robustness.
  • Keywords
    fuzzy set theory; image colour analysis; image motion analysis; image resolution; image sequences; image texture; object detection; Choquet integral; Sugeno integral; aggregation operator; background subtraction; color fusion; color spaces; fuzzy integral; illumination variations; moving object detection; multimedia application; optical motion capture; shadows; video sequences; video-surveillance; Layout; Lighting; Motion detection; Object detection; Pixel; Robustness; Testing; Uncertainty; Video sequences; Video surveillance;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems, 2008. FUZZ-IEEE 2008. (IEEE World Congress on Computational Intelligence). IEEE International Conference on
  • Conference_Location
    Hong Kong
  • ISSN
    1098-7584
  • Print_ISBN
    978-1-4244-1818-3
  • Electronic_ISBN
    1098-7584
  • Type

    conf

  • DOI
    10.1109/FUZZY.2008.4630604
  • Filename
    4630604