• DocumentCode
    3193779
  • Title

    A fast and automatic video object segmentation technique

  • Author

    Lihua, Guo

  • Author_Institution
    Sch. of Electron. & Inf., South China Univ. of Technol., Guangzhou
  • fYear
    2008
  • fDate
    25-27 May 2008
  • Firstpage
    714
  • Lastpage
    717
  • Abstract
    The video object segmentation is a key component of digital video representation, transmission and manipulation, example application including content-based video retrieval, object-based video coding and so on. A fast and automatic video segmentation technique, which aims at foreground and background segmentation via effective combination of color and motion analysis module, is proposed in this paper. Firstly, the watershed segmentation algorithm is employed to provide initial regions according to pixels luminance gradient. Secondly, regions are merged according to their color and motion similarity. Finally, the semantic video object will be obtained after post-processes. The main advantage of this method is its fast and automatic implementation of video object segmentation.
  • Keywords
    content-based retrieval; image colour analysis; image motion analysis; image representation; image resolution; image segmentation; video coding; video retrieval; automatic video object segmentation technique; background segmentation; color analysis module; content-based video retrieval; digital video manipulation; digital video representation; digital video transmission; foreground segmentation; motion analysis module; object-based video coding; pixels luminance gradient; semantic video object; watershed segmentation algorithm; Colored noise; Content based retrieval; Filters; Gaussian noise; Image color analysis; Image segmentation; Information retrieval; Motion analysis; Object segmentation; Video compression;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communications, Circuits and Systems, 2008. ICCCAS 2008. International Conference on
  • Conference_Location
    Fujian
  • Print_ISBN
    978-1-4244-2063-6
  • Electronic_ISBN
    978-1-4244-2064-3
  • Type

    conf

  • DOI
    10.1109/ICCCAS.2008.4657872
  • Filename
    4657872