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» Iterated Graph Cuts for Image Segmentation
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CVPR
2000
IEEE
15 years 1 months ago
Perceptual Grouping and Segmentation by Stochastic Clustering
We use cluster analysis as a unifying principle for problems from low, middle and high level vision. The clustering problem is viewed as graph partitioning, where nodes represent ...
Yoram Gdalyahu, Noam Shental, Daphna Weinshall
PR
2007
189views more  PR 2007»
14 years 9 months ago
Information cut for clustering using a gradient descent approach
We introduce a new graph cut for clustering which we call the Information Cut. It is derived using Parzen windowing to estimate an information theoretic distance measure between p...
Robert Jenssen, Deniz Erdogmus, Kenneth E. Hild II...
86
Voted
FGR
2008
IEEE
346views Biometrics» more  FGR 2008»
15 years 3 months ago
Markov random field models for hair and face segmentation
This paper presents an algorithm for measuring hair and face appearance in 2D images. Our approach starts by using learned mixture models of color and location information to sugg...
Kuang-chih Lee, Dragomir Anguelov, Baris Sumengen,...
CVPR
2011
IEEE
14 years 5 months ago
Biased Normalized Cuts
We present a modification of “Normalized Cuts” to incorporate priors which can be used for constrained image segmentation. Compared to previous generalizations of “Normaliz...
Subhransu Maji, Nisheeth Vishnoi, Jitendra Malik
CVPR
2008
IEEE
15 years 3 months 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...