• DocumentCode
    3186080
  • Title

    Human head-shoulder segmentation

  • Author

    Xin, Hai ; Ai, Haizhou ; Chao, Hui ; Tretter, Daniel

  • Author_Institution
    Comput. Sci. & Technol., Tsinghua Univ., Beijing, China
  • fYear
    2011
  • fDate
    21-25 March 2011
  • Firstpage
    227
  • Lastpage
    232
  • Abstract
    In this paper, an automatic head-shoulder segmentation method for human photos based on graph cut with shape sketch constraint and border detection through learning is presented. We propose a new shape constraint method based upon graph cut for head-shoulder photos. First, a watershed algorithm is used to over segment the photo into superpixels; next, an iterative shape mask guided graph cut algorithm with sketch constraint is applied to the superpixel level graph to get a border that segments the head-shoulder from its background; finally, a border detector, which is trained by AdaBoost, is used to refine the border. Experiments on consumer photo images demonstrate its effectiveness.
  • Keywords
    image segmentation; iterative methods; learning (artificial intelligence); AdaBoost; automatic head-shoulder segmentation method; border detection; human photos; iterative shape mask guided graph cut algorithm; shape sketch constraint method; superpixel level graph; watershed algorithm; Detectors; Face; Humans; Image segmentation; Pixel; Shape; AdaBoost; Border Detection; Graph Cut; Human Segmentation; Shape Sketch;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Automatic Face & Gesture Recognition and Workshops (FG 2011), 2011 IEEE International Conference on
  • Conference_Location
    Santa Barbara, CA
  • Print_ISBN
    978-1-4244-9140-7
  • Type

    conf

  • DOI
    10.1109/FG.2011.5771402
  • Filename
    5771402