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
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