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» Spatially Coherent Clustering Using Graph Cuts
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KDD
2004
ACM
190views Data Mining» more  KDD 2004»
14 years 8 months ago
Kernel k-means: spectral clustering and normalized cuts
Kernel k-means and spectral clustering have both been used to identify clusters that are non-linearly separable in input space. Despite significant research, these methods have re...
Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis
ICMCS
2009
IEEE
180views Multimedia» more  ICMCS 2009»
13 years 5 months ago
Foreground segmentation for static video via multi-core and multi-modal graph cut
We proposed a new foreground detection method using the static cameras. It merges multi-modality into graph cut energy function, and performs much better results than conventional...
Lun-Yu Chang, Winston H. Hsu
ECCV
2010
Springer
13 years 7 months ago
Superpixels and Supervoxels in an Energy Optimization Framework
Many methods for object recognition, segmentation, etc., rely on tessellation of an image into "superpixels". A superpixel is an image patch which is better aligned with ...
Olga Veksler, Yuri Boykov, Paria Mehrani
UAI
2004
13 years 9 months ago
Graph Partition Strategies for Generalized Mean Field Inference
An autonomous variational inference algorithm for arbitrary graphical models requires the ability to optimize variational approximations over the space of model parameters as well...
Eric P. Xing, Michael I. Jordan
ICVGIP
2008
13 years 9 months ago
Visibility Cuts: A System for Rendering Dynamic Virtual Environments
In recent years, the subject of occlusion culling of large 3D environments has received substantial contribution. However the major amount of research into the area has focussed o...
Soumyajit Deb, Ankit Gupta