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.
Cite
@inproceedings{YarkonyF_NIPS_2015,
author = {Julian Yarkony and Charless C. Fowlkes},
title = {Planar Ultrametrics for Image Segmentation},
booktitle = {Neural Information Processing Systems (NIPS)},
year = {2015},
}