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» Kernel k-means: spectral clustering and normalized cuts
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CVPR
2006
IEEE
16 years 8 months ago
Graph Partitioning by Spectral Rounding: Applications in Image Segmentation and Clustering
ct We introduce a new family of spectral partitioning methods. Edge separators of a graph are produced by iteratively reweighting the edges until the graph disconnects into the pre...
David Tolliver, Gary L. Miller
MM
2004
ACM
99views Multimedia» more  MM 2004»
15 years 11 months ago
Locality preserving clustering for image database
It is important and challenging to make the growing image repositories easy to search and browse. Image clustering is a technique that helps in several ways, including image data ...
Xin Zheng, Deng Cai, Xiaofei He, Wei-Ying Ma, Xuey...
ICPR
2008
IEEE
16 years 7 months ago
Multiclass spectral clustering based on discriminant analysis
Many existing spectral clustering algorithms share a conventional graph partitioning criterion: normalized cuts (NC). However, one problem with NC is that it poorly captures the g...
Xi Li, Zhongfei Zhang, Yanguo Wang, Weiming Hu
CVPR
2008
IEEE
16 years 15 days ago
Normalized tree partitioning for image segmentation
In this paper, we propose a novel graph based clustering approach with satisfactory clustering performance and low computational cost. It consists of two main steps: tree fitting...
Jingdong Wang, Yangqing Jia, Xian-Sheng Hua, Chang...

Source Code
2231views
16 years 11 months ago
The Berkeley Segmentation Engine (BSE)
The code is a (good, in my opinion) implementation of a segmentation engine based on normalised cuts (a spectral clustering algorithm) and a pixel affinity matrix calculation algor...
Charless Fowlkes