2013 IEEE Conference on Computer Vision and Pattern Recognition (1997)
June 17, 1997 to June 19, 1997
Jianbo Shi , U.C. Berkeley
Jitendra Malik , U.C. Berkeley
We propose a novel approach for solving the perceptual grouping problem in vision. Rather than focusing on local features and their consistencies in the image data, our approach aims at extracting the global impression of an image. We treat image segmentation as a graph partitioning problem and propose a novel global criterion, the normalized cut, for segmenting the graph. The normalized cut criterion measures both the total dissimilarity between the different groups as well as the total similarity within the groups. We show that an efficient computational technique based on a generalized eigenvalue problem can be used to optimize this criterion. We have applied this approach to segmenting static images and found results very encouraging.
grouping, image segmentation, graph partitioning
Jianbo Shi, Jitendra Malik, "Normalized Cuts and Image Segmentation", 2013 IEEE Conference on Computer Vision and Pattern Recognition, vol. 00, no. , pp. 731, 1997, doi:10.1109/CVPR.1997.609407