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Towards More Efficient and Effective LP-Based Algorithms for MRF Optimization

  • Nikos Komodakis
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6312)

Abstract

This paper proposes a framework that provides significant speed-ups and also improves the effectiveness of general message passing algorithms based on dual LP relaxations. It is applicable to both pairwise and higher order MRFs, as well as to any type of dual relaxation. It relies on combining two ideas. The first one is inspired by algebraic multigrid approaches for linear systems, while the second one employs a novel decimation strategy that carefully fixes the labels for a growing subset of nodes during the course of a dual LP-based algorithm. Experimental results on a wide variety of vision problems demonstrate the great effectiveness of this framework.

Keywords

Dual Variable Master Problem Stereo Match Dual Objective Pairwise Potential 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Supplementary material

978-3-642-15552-9_38_MOESM1_ESM.pdf (66 kb)
Electronic Supplementary Material (67 KB)

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Nikos Komodakis
    • 1
  1. 1.Computer Science DepartmentUniversity of Crete 

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