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Graph cuts segmentation

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  1. Lecture#6: segmentationAnat LevinIntroduction to Computer Vision ClassFall 2009Department of Computer Science and App math, Weizmann Institute of Science.

  2. Graph cuts segmentation http://www.csd.uwo.ca/~yuri/Papers/iccv01.pdf http://www.csd.uwo.ca/~yuri/Papers/iccv99.pdf

  3. Spectral segmentation • Automatic, no user input • group pixels with similar low level cues (color/texture) • No clever high level decisions such as objects identities, just grouping coherent regions http://ai.stanford.edu/~ang/papers/nips01-spectral.pdf http://www.cis.upenn.edu/~jshi/papers/Ncut.pdf http://www.cis.upenn.edu/~jshi/papers/pami_ncut.pdf

  4. Normalized Cuts

  5. Original Image and rows from the weight matrix

  6. Eigen vectors

  7. Segmentation

  8. How many groups?

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