Generalized Fast Approximate Energy Minimization via Graph Cuts: Alpha-Expansion Beta-Shrink Moves
Computer Vision and Pattern Recognition
2012-02-19 v1 Artificial Intelligence
Abstract
We present alpha-expansion beta-shrink moves, a simple generalization of the widely-used alpha-beta swap and alpha-expansion algorithms for approximate energy minimization. We show that in a certain sense, these moves dominate both alpha-beta-swap and alpha-expansion moves, but unlike previous generalizations the new moves require no additional assumptions and are still solvable in polynomial-time. We show promising experimental results with the new moves, which we believe could be used in any context where alpha-expansions are currently employed.
Keywords
Cite
@article{arxiv.1108.5710,
title = {Generalized Fast Approximate Energy Minimization via Graph Cuts: Alpha-Expansion Beta-Shrink Moves},
author = {Mark Schmidt and Karteek Alahari},
journal= {arXiv preprint arXiv:1108.5710},
year = {2012}
}
Comments
Conference on Uncertainty in Artificial Intelligence (2011)