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102
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TIP
2008
133views more  TIP 2008»
15 years 22 days ago
A Recursive Model-Reduction Method for Approximate Inference in Gaussian Markov Random Fields
This paper presents recursive cavity modeling--a principled, tractable approach to approximate, near-optimal inference for large Gauss-Markov random fields. The main idea is to su...
Jason K. Johnson, Alan S. Willsky
IMAMS
2003
125views Mathematics» more  IMAMS 2003»
15 years 2 months ago
A Graph-Spectral Method for Surface Height Recovery
This paper describes a graph-spectral method for 3D surface integration. The algorithm takes as its input a 2D field of surface normal estimates, delivered, for instance, by a sh...
Antonio Robles-Kelly, Edwin R. Hancock
IBPRIA
2003
Springer
15 years 6 months ago
Segmentation of Curvilinear Objects Using a~Watershed-Based Curve Adjacency Graph
Abstract. This paper presents a general framework to segment curvilinear objects in 2D images. A pre-processing step relies on mathematical morphology to obtain a connected line wh...
Thierry Géraud
ECCV
2006
Springer
16 years 2 months ago
A Comparative Study of Energy Minimization Methods for Markov Random Fields
One of the most exciting advances in early vision has been the development of efficient energy minimization algorithms. Many early vision tasks require labeling each pixel with som...
Richard Szeliski, Ramin Zabih, Daniel Scharstein, ...
152
Voted
CVPR
2009
IEEE
15 years 11 months ago
Markov Chain Monte Carlo Combined with Deterministic Methods for Markov Random Field Optimization
Many vision problems have been formulated as en- ergy minimization problems and there have been signif- icant advances in energy minimization algorithms. The most widely-used energ...
Wonsik Kim (Seoul National University), Kyoung Mu ...