• DocumentCode
    3389276
  • Title

    Moving target detection based on Genetic K-means Algorithm

  • Author

    Xiuman, Duan ; Guoxia, Sun ; Tao, Yang

  • Author_Institution
    Sch. of Inf. Sci. & Eng., Shandong Univ., Jinan, China
  • fYear
    2011
  • fDate
    25-28 Sept. 2011
  • Firstpage
    819
  • Lastpage
    822
  • Abstract
    Recently, the research on extracting moving objects from video sequences in the current computer vision applications is very popular. A new method based on genetic k-means algorithm from Gaussian mixture model (GMM) to deal with moving target of video image was purposed in this paper. The described method in this paper is learned from clustering idea, which is very different from traditional way. According to Genetic K-means Algorithm, by clustering of pixels on the timeline, the background could be described through several clusters. On the basic of these clusters, moving target detection could be done. Simulation experiment showed that the method could give a good result for the moving target detection.
  • Keywords
    Gaussian processes; computer vision; object detection; GMM; Gaussian mixture model; computer vision; genetic K-means algorithm; moving target detection; target detection moving; Biological cells; Clustering algorithms; Computational modeling; Computer vision; Genetics; Object detection; Vectors; background modeling; genetic k-means algorithm; moving target detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communication Technology (ICCT), 2011 IEEE 13th International Conference on
  • Conference_Location
    Jinan
  • Print_ISBN
    978-1-61284-306-3
  • Type

    conf

  • DOI
    10.1109/ICCT.2011.6157992
  • Filename
    6157992