Fast Planar Correlation Clustering for Image Segmentation
Abstract
We describe a new optimization scheme for finding high-quality clusterings in planar graphs that uses weighted perfect matching as a subroutine. Our method provides lower-bounds on the energy of the optimal correlation clustering that are typically fast to compute and tight in practice. We demonstrate our algorithm on the problem of image segmentation where this approach outperforms existing global optimization techniques in minimizing the objective and is competitive with the state of the art in producing high-quality segmentations.
Cite
Text
Yarkony et al. "Fast Planar Correlation Clustering for Image Segmentation." European Conference on Computer Vision, 2012. doi:10.1007/978-3-642-33783-3_41Markdown
[Yarkony et al. "Fast Planar Correlation Clustering for Image Segmentation." European Conference on Computer Vision, 2012.](https://mlanthology.org/eccv/2012/yarkony2012eccv-fast/) doi:10.1007/978-3-642-33783-3_41BibTeX
@inproceedings{yarkony2012eccv-fast,
title = {{Fast Planar Correlation Clustering for Image Segmentation}},
author = {Yarkony, Julian and Ihler, Alexander and Fowlkes, Charless C.},
booktitle = {European Conference on Computer Vision},
year = {2012},
pages = {568-581},
doi = {10.1007/978-3-642-33783-3_41},
url = {https://mlanthology.org/eccv/2012/yarkony2012eccv-fast/}
}