• DocumentCode
    2399532
  • Title

    Transductive object cutout

  • Author

    Cui, Jingyu ; Yang, Qiong ; Wen, Fang ; Wu, Qiying ; Zhang, Changshui ; Van Gool, Luc ; Tang, Xiaoou

  • Author_Institution
    Tsinghua Univ., Beijing
  • fYear
    2008
  • fDate
    23-28 June 2008
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    In this paper, we address the issue of transducing the object cutout model from an example image to novel image instances. We observe that although object and background are very likely to contain similar colors in natural images, it is much less probable that they share similar color configurations. Motivated by this observation, we propose a local color pattern model to characterize the color configuration in a robust way. Additionally, we propose an edge profile model to modulate the contrast of the image, which enhances edges along object boundaries and attenuates edges inside object or background. The local color pattern model and edge model are integrated in a graph-cut framework. Higher accuracy and improved robustness of the proposed method are demonstrated through experimental comparison with state-of-the-art algorithms.
  • Keywords
    edge detection; graph theory; image colour analysis; image enhancement; object detection; color configuration; edge enhancement; edge profile model; graph-cut framework; image instance; local color pattern model; natural image colour analysis; object boundary; transductive object cutout model; Asia; Histograms; Image segmentation; Learning systems; Machine learning; Machine learning algorithms; Object segmentation; Optimized production technology; Pixel; Robustness;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition, 2008. CVPR 2008. IEEE Conference on
  • Conference_Location
    Anchorage, AK
  • ISSN
    1063-6919
  • Print_ISBN
    978-1-4244-2242-5
  • Electronic_ISBN
    1063-6919
  • Type

    conf

  • DOI
    10.1109/CVPR.2008.4587589
  • Filename
    4587589