Talk:Segmentation-based object categorization

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Ncut

In the section "The Ncut algorithm" the value "D" is introduced without explanation. Also, none of the "figures" actually occur in the article.

To follow this comment, the "ncut algorithm" section should refer/link to the degree and adjacency matrix of a graph (or even the Laplacian matrix) when defining D and W, as well as the algebraic connectivity of the graph when referencing the second smallest eigenvalue. 70.166.151.52 (talk) 16:42, 15 February 2017 (UTC)[reply]

Are arbitrary values allowed for the weights (similarity measures), or are they restricted to some range (non-negative, [0,1], ...)? It seems to me that negative weights can potentially invert the sign of some of the fraction denominators causing semantic havoc. Mspreitz (talk) 02:40, 11 April 2011 (UTC)[reply]

The denominators beg the question of what is on the diagonal of the w matrix. Mspreitz (talk) 03:21, 11 April 2011 (UTC)[reply]

Rename or merge with Segmentation (image processing)

The distinction between this article and Segmentation (image processing) appears unclear. What about either:

  • Renaming this article into "Graph-based image segmentation" (or similar), to highlight the focus on graph-based methods, or ...
  • Merge this article with Segmentation (image processing), since both deals with the same overall topic?

Any comments? --Fredrik Orderud (talk) 20:47, 24 August 2008 (UTC)[reply]

Bipartitioning a graph with the eigenvector

How does one "use the eigenvector with the smallest eigenvalue to bipartition the graph"? Is there another article to which we could link that would provide those details? --76.27.96.159 (talk) 04:29, 10 December 2008 (UTC)[reply]

Shi and Malik, 2000 advice to use the second smallest eigenvector to bipartition the graph — Preceding unsigned comment added by Cle003 (talk • contribs) 13:43, 4 May 2016 (UTC)[reply]

Example

Hm, there is no "Figures 1-7" 129.27.201.116 (talk) —Preceding undated comment added 09:59, 13 December 2010 (UTC).[reply]

Extention of NCut in 3D for object: Tonny, Z., Laurendeau, D., Giguere, P., Gagne, C., 2014. 3D-NCuts: Adapting Normalized Cuts to 3D Triangulated Surface Segmentation. Computer Graphics Theory and Applications (GRAPP), 2014 International Conference on, 1-9.

Application in transportation network partitionning: Ji, Y., Geroliminis, N., 2012. On the spatial partitioning of urban transportation networks. Transportation Research Part B : Methodological, 46 (10), 1639-1656. — Preceding unsigned comment added by Cle003 (talk • contribs) 13:47, 4 May 2016 (UTC)[reply]

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