Abstract
We describe a scheme for solving Energy Minimization problems, which is based on the A * algorithm accomplished with appropriately chosen LP-relaxations as heuristic functions. The proposed scheme is quite general and therefore can not be applied directly for real computer vision tasks. It is rather a framework, which allows to study some properties of Energy Minimization tasks and related LP-relaxations. However, it is possible to simplify it in such a way, that it can be used as a stop criterion for LP based iterative algorithms. Its main advantage is that it is exact – i.e. it never produces a discrete solution that is not globally optimal. In practice it is often able to find the optimal discrete solution even if the used LP-solver does not reach the global optimum of the corresponding LP-relaxation. Consequently, for many Energy Minimization problems it is not necessary to solve the corresponding LP-relaxations exactly.
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Schlesinger, D. (2009). General Search Algorithms for Energy Minimization Problems. In: Cremers, D., Boykov, Y., Blake, A., Schmidt, F.R. (eds) Energy Minimization Methods in Computer Vision and Pattern Recognition. EMMCVPR 2009. Lecture Notes in Computer Science, vol 5681. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03641-5_7
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DOI: https://doi.org/10.1007/978-3-642-03641-5_7
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