• DocumentCode
    2919568
  • Title

    Nonlocal matting

  • Author

    Lee, Philip ; Wu, Ying

  • Author_Institution
    Northwestern Univ., Evanston, IL, USA
  • fYear
    2011
  • fDate
    20-25 June 2011
  • Firstpage
    2193
  • Lastpage
    2200
  • Abstract
    This work attempts to considerably reduce the amount of user effort in the natural image matting problem. The key observation is that the nonlocal principle, introduced to denoise images, can be successfully applied to the alpha matte to obtain sparsity in matte representation, and therefore dramatically reduce the number of pixels a user needs to manually label. We show how to avoid making the user provide redundant and unnecessary input, develop a method for clustering the image pixels for the user to label, and a method to perform high-quality matte extraction. We show that this algorithm is therefore faster, easier, and higher quality than state of the art methods.
  • Keywords
    feature extraction; image denoising; image representation; pattern clustering; high-quality matte extraction; image denoising; image pixel clustering; matte representation; natural image matting problem; nonlocal matting; nonlocal principle; pixel reduction; Accuracy; Cameras; Clustering algorithms; Humans; Image color analysis; Kernel; Laplace equations;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on
  • Conference_Location
    Providence, RI
  • ISSN
    1063-6919
  • Print_ISBN
    978-1-4577-0394-2
  • Type

    conf

  • DOI
    10.1109/CVPR.2011.5995665
  • Filename
    5995665