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» Spatially Coherent Clustering Using Graph Cuts
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BMVC
2010
13 years 3 months ago
Patch-Cuts: A Graph-Based Image Segmentation Method Using Patch Features and Spatial Relations
In this paper, we present a graph-based image segmentation method (patch-cuts) that incorporates features and spatial relations obtained from image patches. In the first step, pat...
Gerd Brunner, Deepak Roy Chittajallu, Uday Kurkure...
JMMA
2010
162views more  JMMA 2010»
13 years 6 days ago
Co-clustering Documents and Words by Minimizing the Normalized Cut Objective Function
This paper follows a word-document co-clustering model independently introduced in 2001 by several authors such as I.S. Dhillon, H. Zha and C. Ding. This model consists in creatin...
Charles-Edmond Bichot
ICIP
2006
IEEE
14 years 7 months ago
Background Modeling from GMM Likelihood Combined with Spatial and Color Coherency
This paper proposes to combine spatial and color coherency with the pixel-wise GMM to determine the background model. We first represent each pixel with a hybrid feature vector, w...
Sheng-Yan Yang, Chiou-Ting Hsu
PAMI
2007
202views more  PAMI 2007»
13 years 4 months ago
Weighted Graph Cuts without Eigenvectors A Multilevel Approach
—A variety of clustering algorithms have recently been proposed to handle data that is not linearly separable; spectral clustering and kernel k-means are two of the main methods....
Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis
ICML
2009
IEEE
14 years 6 months ago
Spectral clustering based on the graph p-Laplacian
We present a generalized version of spectral clustering using the graph p-Laplacian, a nonlinear generalization of the standard graph Laplacian. We show that the second eigenvecto...
Matthias Hein, Thomas Bühler