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» Graph Cuts and Efficient N-D Image Segmentation
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FGR
2008
IEEE
346views Biometrics» more  FGR 2008»
14 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
13 years 4 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
PAMI
2006
226views more  PAMI 2006»
13 years 8 months ago
Graph Partitioning Active Contours (GPAC) for Image Segmentation
In this paper we introduce new type of variational segmentation cost functions and associated active contour methods that are based on pairwise similarities or dissimilarities of t...
Baris Sumengen, B. S. Manjunath
CVPR
2008
IEEE
14 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...
ICCV
2009
IEEE
15 years 1 months ago
Extending Continuous Cuts: Anisotropic Metrics and Expansion Moves
The concept of graph cuts is by now a standard method for all sorts of low level vision problems. Its popularity is largely due to the fact that globally or near globally optimal...
Carl Olsson, Martin Byr¨od, Niels Chr. Overgaard,...