Planar Ultrametrics for Image Segmentation

Julian E Yarkony; Charless Fowlkes

NeurIPS 2015poster22 citations

Planar Ultrametrics for Image Segmentation

Abstract

We study the problem of hierarchical clustering on planar graphs. We formulate this in terms of finding the closest ultrametric to a specified set of distances and solve it using an LP relaxation that leverages minimum cost perfect matching as a subroutine to efficiently explore the space of planar partitions. We apply our algorithm to the problem of hierarchical image segmentation.

BibTeX

@inproceedings{NIPS2015_3416a75f,
 author = {Yarkony, Julian E and Fowlkes, Charless},
 booktitle = {Advances in Neural Information Processing Systems},
 editor = {C. Cortes and N. Lawrence and D. Lee and M. Sugiyama and R. Garnett},
 pages = {},
 publisher = {Curran Associates, Inc.},
 title = {Planar Ultrametrics for Image Segmentation},
 url = {https://proceedings.neurips.cc/paper_files/paper/2015/file/3416a75f4cea9109507cacd8e2f2aefc-Paper.pdf},
 volume = {28},
 year = {2015}
}