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Transformation of General Binary MRF Minimization to the First Order Case (2011)
| Venue: | IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI |
| Citations: | 29 - 3 self |
BibTeX
@ARTICLE{Ishikawa11transformationof,
author = {Hiroshi Ishikawa},
title = {Transformation of General Binary MRF Minimization to the First Order Case},
journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI},
year = {2011},
pages = {1234--1249}
}
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Abstract
Abstract—We introduce a transformation of general higher-order Markov random field with binary labels into a first-order one that has the same minima as the original. Moreover, we formalize a framework for approximately minimizing higher-order multilabel MRF energies that combines the new reduction with the fusion-move and QPBO algorithms. While many computer vision problems today are formulated as energy minimization problems, they have mostly been limited to using first-order energies, which consist of unary and pairwise clique potentials, with a few exceptions that consider triples. This is because of the lack of efficient algorithms to optimize energies with higher-order interactions. Our algorithm challenges this restriction that limits the representational power of the models so that higher-order energies can be used to capture the rich statistics of natural scenes. We also show that some minimization methods can be considered special cases of the present framework, as well as comparing the new method experimentally with other such techniques. Index Terms—Energy minimization, pseudo-Boolean function, higher order MRFs, graph cuts. F 1
Keyphrases
first order case general binary mrf minimization efficient algorithm rich statistic graph cut many computer vision problem today higher-order interaction present framework natural scene general higher-order markov random field new reduction index term energy minimization minimization method first-order one first-order energy order mrfs energy minimization problem pairwise clique potential binary label new method representational power pseudo-boolean function special case higher-order energy higher-order multilabel mrf
