Graph Cuts with Interacting Edge Costs - Examples, Approximations, and Algorithms
Data Structures and Algorithms
2016-03-29 v4 Computer Vision and Pattern Recognition
Discrete Mathematics
Optimization and Control
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.
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Cite
@article{arxiv.1402.0240,
title = {Graph Cuts with Interacting Edge Costs - Examples, Approximations, and Algorithms},
author = {Stefanie Jegelka and Jeff Bilmes},
journal= {arXiv preprint arXiv:1402.0240},
year = {2016}
}
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46 pages