The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Normalized cuts and image segmentation
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 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.
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Golub, G. (2012) · doi:10.56021/9781421407944 · Cited by 34,505
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Interactive graph cuts for optimal boundary & region segmentation of objects in N-D images
Boykov, Y. Y., & Jolly, M.-P. (2002) · Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001 · doi:10.1109/iccv.2001.937505 · Cited by 3,674
Ranking-based clustering of heterogeneous information networks with star network schema
Sun, Y., Yu, Y., & Han, J. (2009) · Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining · doi:10.1145/1557019.1557107 · Cited by 513
Chen, M., Zhang, Z., Wang, T., Backes, M., Humbert, M., & Zhang, Y. (2022) · Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security · doi:10.1145/3548606.3559352 · Cited by 133
Discovering genetic ancestry using spectral graph theory
Lee, A. B., Luca, D., Klei, L., Devlin, B., & Roeder, K. (2010) · Genetic Epidemiology · doi:10.1002/gepi.20434 · Cited by 108
“Finding the partition with the minimum cut is a well-studied problem; however, the minimum cut criterion favors separating individual vertices or ‘‘outliers’’ from the rest of the graph [Shi and Malik, 1997].”
Background
Metadata
- Authors
- Shi, J., & Malik, J.
- Venue
- Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition
- Publisher
- IEEE Comput. Soc
- Published
- 2002-11-22
- Pages
- 731-737
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W2140000690
- Cited by
- 849
- References
- 1
- FWCI
- 31.57
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Shi, J., & Malik, J. (2002). Normalized cuts and image segmentation. Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition. https://doi.org/10.1109/cvpr.1997.609407
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