Convergent Tree-Reweighted Message Passing for Energy Minimization

BT Research · University College London

PubMed
Indexed incrossrefpubmed

Abstract

Algorithms for discrete energy minimization are of fundamental importance in computer vision. In this paper, we focus on the recent technique proposed by Wainwright et al. [33]--tree-reweighted max-product message passing (TRW). It was inspired by the problem of maximizing a lower bound on the energy. However, the algorithm is not guaranteed to increase this bound--it may actually go down. In addition, TRW does not always converge. We develop a modification of this algorithm which we call sequential tree-reweighted message passing. Its main property is that the bound is guaranteed not to decrease. We also give a weak tree agreement condition which characterizes local maxima of the bound with respect to TRW…

Citation impact

1,122
total citations
FWCI
51.21
Percentile
100%
References
42
Citations per year

Authors

1

Topics & keywords

Keywords
  • Message passing
  • Tree (set theory)
  • Computer science
  • Upper and lower bounds
  • Algorithm
  • Belief propagation
  • Energy minimization
  • k-minimum spanning tree
UN Sustainable Development Goals
  • Affordable and clean energy
No related works found for this paper.

Funding