Title :
A spectral method for image co-segmentation
Author :
Chen, Tiantang ; Li, Hongliang
Author_Institution :
Univ. of Electron. Sci. & Technol. of China, Chengdu, China
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;
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
DOI :
10.1109/ICCPS.2011.6092301