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PAMI
2007
176views more  PAMI 2007»
15 years 6 months ago
Approximate Labeling via Graph Cuts Based on Linear Programming
A new framework is presented for both understanding and developing graph-cut based combinatorial algorithms suitable for the approximate optimization of a very wide class of MRFs ...
Nikos Komodakis, Georgios Tziritas
IBPRIA
2003
Springer
15 years 11 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 8 months ago
Efficient Belief Propagation with Learned Higher-Order Markov Random Fields
Belief propagation (BP) has become widely used for low-level vision problems and various inference techniques have been proposed for loopy graphs. These methods typically rely on a...
Xiangyang Lan, Stefan Roth, Daniel P. Huttenlocher...
ECCV
2006
Springer
16 years 8 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, ...
CVPR
2009
IEEE
16 years 4 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 ...