2000 NormalizedCutsAndImageSeg

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Subject Headings: Normalized Cuts Algorithm, Graph Partitioning, Segmentation-based Object Categorization.

Notes

Cited By

2011

2000

  • (Stauffer & Grimson, 2000) ⇒ Stauffer, and W.E.L. Grimson, (2000). “Learning patterns of activity using real-time tracking" In: IEEE Transactions on Pattern Analysis and Machine Intelligence]], 22(8). [doi:10.1109/34.868677]

Quotes

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 applied this approach to segmenting static images, as well as motion sequences, and found the results to be very encouraging Index Terms

References


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 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
2000 NormalizedCutsAndImageSegJianbo Shi
Jitendra Malik
Normalized Cuts and Image Segmentationhttp://www.cs.berkeley.edu/~malik/papers/SM-ncut.pdf10.1109/34.868688