• DocumentCode
    2512308
  • Title

    A spectral method for image co-segmentation

  • Author

    Chen, Tiantang ; Li, Hongliang

  • Author_Institution
    Univ. of Electron. Sci. & Technol. of China, Chengdu, China
  • fYear
    2011
  • fDate
    21-23 Oct. 2011
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    In this paper, we propose a spectral method to address the problem of image co-segmentation. Our idea is motivated by the Normalized Cut algorithm and spectral clustering. By defining a superpixel graph over the given image pair and introducing the successful ideas of Ncut formulation, we successfully transform the co-segmentation problem into a Rayleigh quotient problem, which can be solved by eigen-decomposition. Then we utilize spectral clustering to classify the pixels in each image and obtain the common objects of the image pair. Experimental results have demonstrated the effectiveness of the proposed method.
  • Keywords
    eigenvalues and eigenfunctions; graph theory; image segmentation; pattern clustering; Ncut formulation; Rayleigh quotient problem; eigendecomposition; image cosegmentation; normalized cut algorithm; spectral clustering; spectral method; superpixel graph; Cost function; Image color analysis; Image edge detection; Image segmentation; Laplace equations; Matrices; Minimization; Co-segmentation; Ncut; eigenvector; spectral clustering;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Problem-Solving (ICCP), 2011 International Conference on
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-1-4577-0602-8
  • Electronic_ISBN
    978-1-4577-0601-1
  • Type

    conf

  • DOI
    10.1109/ICCPS.2011.6092301
  • Filename
    6092301