WERNER, T.: A Linear Programming Approach to Max-sum Problem: A review. [Research Report]. Prague: CTU, Faculty of Electrical Engineering, Center for Machine Perception, 2005. CTU-CMP--2005--25. 40 p. ISSN 1213-2365.
The max-sum labeling problem, de ned as maximizing a sum of functions of pairs of discrete variables, is a general optimization problem with numerous applications, e.g., computing MAP assignments of a Markov random eld. We review a not widely known approach to the problem based on linear programming relaxation, developed by Schlesinger et al. in 1976. We also show how this old approach contributes to more recent results, most importantly by Wainwright et al. In particular, we review Schlesinger's upper bound on the max-sum criterion, its minimization by equivalent transformations, its relation to constraint satisfaction problem, how it can be understood as a linear programming relaxation, and three kinds of consistency necessary for optimality of the upper bound. As special cases, we revisit problems with two labels and supermodular problems. We describe two algorithms for decreasing the upper bound. We present an example application to structural image analysis.
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en
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Center for Machine Perception, Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University
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Research Reports of CMP. 2005, No. 25
eng
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Research Subject Categories::TECHNOLOGY::Electrical engineering, electronics and photonics
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structural pattern recognition
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Markov random fields
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linear programming
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computer vision
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constraint satisfaction
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belief propagation
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max-sum
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max-product
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min-sum
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min-product
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supermodular optimization
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dc.title
A Linear Programming Approach to Max-sum Problem: A Review