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ECCV
2006
Springer
11 years 3 months ago
Comparison of Energy Minimization Algorithms for Highly Connected Graphs
Algorithms for discrete energy minimization play a fundamental role for low-level vision. Known techniques include graph cuts, belief propagation (BP) and recently introduced tree-...
Vladimir Kolmogorov, Carsten Rother
EMMCVPR
2001
Springer
10 years 5 months ago
An Experimental Comparison of Min-cut/Max-flow Algorithms for Energy Minimization in Vision
After [15, 31, 19, 8, 25, 5] minimum cut/maximum flow algorithms on graphs emerged as an increasingly useful tool for exact or approximate energy minimization in low-level vision...
Yuri Boykov, Vladimir Kolmogorov
ICCV
2009
IEEE
9 years 11 months ago
Minimizing energy functions on 4-connected lattices using elimination
We describe an energy minimization algorithm for functions defined on 4-connected lattices, of the type usually encountered in problems involving images. Such functions are often ...
Peter Carr, Richard Hartley
ECCV
2002
Springer
11 years 3 months ago
What Energy Functions Can Be Minimized via Graph Cuts?
In the last few years, several new algorithms based on graph cuts have been developed to solve energy minimization problems in computer vision. Each of these techniques constructs...
Vladimir Kolmogorov, Ramin Zabih
DAGM
2008
Springer
10 years 3 months ago
MAP-Inference for Highly-Connected Graphs with DC-Programming
The design of inference algorithms for discrete-valued Markov Random Fields constitutes an ongoing research topic in computer vision. Large state-spaces, none-submodular energy-fun...
Jörg H. Kappes, Christoph Schnörr
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