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» Supervised Image Segmentation Using Markov Random Fields
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IPMI
2009
Springer
16 years 19 days ago
Non-rigid Image Registration with Uniform Spherical Structure Patterns
Abstract. Non-rigid image registration is a challenging task in medical image analysis. In recent years, there are two essential issues. First, intensity similarity is not necessar...
Albert C. S. Chung, Shu Liao
CVIU
2007
136views more  CVIU 2007»
14 years 11 months ago
MAP ZDF segmentation and tracking using active stereo vision: Hand tracking case study
A maximum a posterior probability zero disparity filter (MAP ZDF) ensures coordinated stereo fixation upon an arbitrarily moving, rotating, re-configuring hand, performing mark...
Andrew Dankers, Nick Barnes, Alexander Zelinsky
CVPR
2006
IEEE
16 years 1 months ago
Stereo Matching with Symmetric Cost Functions
Recently, many global stereo methods have achieved good results by modeling a disparity surface as a Markov random field (MRF) and by solving an optimization problem with various ...
Kuk-Jin Yoon, In-So Kweon
KDD
2004
ACM
132views Data Mining» more  KDD 2004»
16 years 6 days ago
A probabilistic framework for semi-supervised clustering
Unsupervised clustering can be significantly improved using supervision in the form of pairwise constraints, i.e., pairs of instances labeled as belonging to same or different clu...
Sugato Basu, Mikhail Bilenko, Raymond J. Mooney
UAI
2008
15 years 1 months ago
Projected Subgradient Methods for Learning Sparse Gaussians
Gaussian Markov random fields (GMRFs) are useful in a broad range of applications. In this paper we tackle the problem of learning a sparse GMRF in a high-dimensional space. Our a...
John Duchi, Stephen Gould, Daphne Koller