• DocumentCode
    2619163
  • Title

    Accurate silhouette segmentation using motion detection and graph cuts

  • Author

    Chen, Daniel ; Denman, Simon ; Fookes, Clinton

  • Author_Institution
    Image & Video Res. Lab., Queensland Univ. of Technol., Brisbane, QLD, Australia
  • fYear
    2010
  • fDate
    10-13 May 2010
  • Firstpage
    81
  • Lastpage
    84
  • Abstract
    Acquiring accurate silhouettes has many applications in computer vision. This is usually done through motion detection, or a simple background subtraction under highly controlled environments (i.e. chroma-key backgrounds). Lighting and contrast issues in typical outdoor or office environments make accurate segmentation very difficult in these scenes. In this paper, gradients are used in conjunction with intensity and colour to provide a robust segmentation of motion, after which graph cuts are utilised to refine the segmentation. The results presented using the ETISEO database demonstrate that an improved segmentation is achieved through the combined use of motion detection and graph cuts, particularly in complex scenes.
  • Keywords
    graph theory; image segmentation; motion estimation; visual databases; ETISEO database; accurate silhouette segmentation; computer vision application; graph cuts; motion detection; robust segmentation; Back; Biomedical imaging; Image color analysis; Image edge detection; Image segmentation; Motion segmentation; Real time systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Sciences Signal Processing and their Applications (ISSPA), 2010 10th International Conference on
  • Conference_Location
    Kuala Lumpur
  • Print_ISBN
    978-1-4244-7165-2
  • Type

    conf

  • DOI
    10.1109/ISSPA.2010.5605501
  • Filename
    5605501