Edited by author 04-12-2002 11:24 PM
Hi all, this paper by Yair Weiss is an overview of recent work in spectral segmentation methods. It will give a good introduction to the talk, but there is much more to discuss than just this paper. Recent work by Andrew Ng, Marina Meila, Ravi Kannan, and others is also interesting and relevant. Andrew Ng's paper especially makes nice arguments for the methods from the perspective of perfectly separated data.

Here are pointers to the papers referenced in Weiss' paper, and others of interest:

• Normalized cuts and image segmentation (Shi & Malik)
• Learning segmentation with random walks (Meila & Shi)
• A factorization approach to grouping (Perona & Freeman)
• On clusterings -- good, bad, and spectral (Kannan, Vempala, Vetta)
• Feature grouping by relocalisation of eigenvectors of the proximity matrix (Scott & Longuet-Higgins)
• On spectral clustering: analysis and an algorithm (Ng, Jordan, Weiss)
  

In Yair Weiss' paper there is at least one typo, in section 2.1. The phrase "between cluster affinity B is zero" should be "between cluster affinity *C* is zero".

The topic of this board still says "Mean Shift", due to a change in my choice of paper.