Mathematical Programming

, Volume 162, Issue 1–2, pp 241–282 | Cite as

Graph cuts with interacting edge weights: examples, approximations, and algorithms

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Abstract

We study an extension of the classical graph cut problem, wherein we replace the modular (sum of edge weights) cost function by a submodular set function defined over graph edges. Special cases of this problem have appeared in different applications in signal processing, machine learning, and computer vision. In this paper, we connect these applications via the generic formulation of “cooperative graph cuts”, for which we study complexity, algorithms, and connections to polymatroidal network flows. Finally, we compare the proposed algorithms empirically.

Mathematics Subject Classification

68R10 68T45 68Q25 

Supplementary material

10107_2016_1038_MOESM_ESM.pdf (1.5 mb)
Supplementary material 1 (pdf 1541 KB)

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Copyright information

© Springer-Verlag Berlin Heidelberg and Mathematical Optimization Society 2016

Authors and Affiliations

  1. 1.Department of EECSMassachusetts Institute of TechnologyCambridgeUSA
  2. 2.Department of EEUniversity of WashingtonSeattleUSA

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