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Parallel Multicut Segmentation via Dual Decomposition

  • Julian Yarkony
  • Thorsten Beier
  • Pierre Baldi
  • Fred A. Hamprecht
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8983)

Abstract

We propose a new outer relaxation of the multicut polytope, along with a dual decomposition approach for correlation clustering and multicut segmentation, for general graphs. Each subproblem is a minimum \(st\)-cut problem and can thus be solved efficiently. An optimal reparameterization is found using subgradients and affords a new characterization of the basic LP relaxation of the multicut problem, as well as informed decoding heuristics. The algorithm we propose for solving the problem distributes the computation and is amenable to a parallel implementation.

Keywords

Dual decomposition Multi-cut segmentation Correlation clustering 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Julian Yarkony
    • 1
    • 2
  • Thorsten Beier
    • 1
  • Pierre Baldi
    • 2
  • Fred A. Hamprecht
    • 1
  1. 1.Heidelberg Collaboratory for Image Processing (HCI)University of HeidelbergHeidelbergGermany
  2. 2.Department of Computer ScienceUniversity of California, IrvineIrvineUSA

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