An Efficient Fusion Move Algorithm for the Minimum Cost Lifted Multicut Problem
Abstract
Many computer vision problems can be cast as an optimization problem whose feasible solutions are decompositions of a graph. The minimum cost lifted multicut problem is such an optimization problem. Its objective function can penalize or reward all decompositions for which any given pair of nodes are in distinct components. While this property has many potential applications, such applications are hampered by the fact that the problem is NP-hard. We propose a fusion move algorithm for computing feasible solutions, better and more efficiently than existing algorithms. We demonstrate this and applications to image segmentation, obtaining a new state of the art for a problem in biological image analysis.
Cite
Text
Beier et al. "An Efficient Fusion Move Algorithm for the Minimum Cost Lifted Multicut Problem." European Conference on Computer Vision, 2016. doi:10.1007/978-3-319-46475-6_44Markdown
[Beier et al. "An Efficient Fusion Move Algorithm for the Minimum Cost Lifted Multicut Problem." European Conference on Computer Vision, 2016.](https://mlanthology.org/eccv/2016/beier2016eccv-efficient/) doi:10.1007/978-3-319-46475-6_44BibTeX
@inproceedings{beier2016eccv-efficient,
title = {{An Efficient Fusion Move Algorithm for the Minimum Cost Lifted Multicut Problem}},
author = {Beier, Thorsten and Andres, Björn and Köthe, Ullrich and Hamprecht, Fred A.},
booktitle = {European Conference on Computer Vision},
year = {2016},
pages = {715-730},
doi = {10.1007/978-3-319-46475-6_44},
url = {https://mlanthology.org/eccv/2016/beier2016eccv-efficient/}
}