(Enter summary)
Abstract: 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... (Update)
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BibTeX entry: (Update)
J. Shi and J. Malik. Normalized cuts and image segmentation. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR'97), pages 731--737, 1997. http://citeseer.ist.psu.edu/shi97normalized.html More
@article{ shi00normalized,
author = "Jianbo Shi and Jitendra Malik",
title = "Normalized Cuts and Image Segmentation",
journal = "IEEE Transactions on Pattern Analysis and Machine Intelligence",
volume = "22",
number = "8",
pages = "888-905",
year = "2000",
url = "citeseer.ist.psu.edu/shi97normalized.html" }
Citations (may not include all citations):
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Algorithms for Clustering Data (context) - Jain, Dubes - 1988
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Visual Reconstruction (context) - Blake, Zisserman - 1987
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