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CVPR
2009
IEEE
15 years 11 days ago
Alphabet SOUP: A Framework for Approximate Energy Minimization
Many problems in computer vision can be modeled using conditional Markov random fields (CRF). Since finding the maximum a posteriori (MAP) solution in such models is NP-hard, mu...
Stephen Gould (Stanford University), Fernando Amat...
ECCV
2008
Springer
14 years 7 months ago
Efficiently Learning Random Fields for Stereo Vision with Sparse Message Passing
As richer models for stereo vision are constructed, there is a growing interest in learning model parameters. To estimate parameters in Markov Random Field (MRF) based stereo formu...
Jerod J. Weinman, Lam Tran, Christopher J. Pal
CVPR
2006
IEEE
14 years 7 months ago
Solving Markov Random Fields using Second Order Cone Programming Relaxations
This paper presents a generic method for solving Markov random fields (MRF) by formulating the problem of MAP estimation as 0-1 quadratic programming (QP). Though in general solvi...
M. Pawan Kumar, Philip H. S. Torr, Andrew Zisserma...
AMAI
2004
Springer
13 years 10 months ago
New Look-Ahead Schemes for Constraint Satisfaction
This paper presents new look-ahead schemes for backtracking search when solving constraint satisfaction problems. The look-ahead schemes compute a heuristic for value ordering and...
Kalev Kask, Rina Dechter, Vibhav Gogate
CVPR
2006
IEEE
13 years 11 months ago
Measure Locally, Reason Globally: Occlusion-sensitive Articulated Pose Estimation
Part-based tree-structured models have been widely used for 2D articulated human pose-estimation. These approaches admit efficient inference algorithms while capturing the import...
Leonid Sigal, Michael J. Black