Planar Ultrametrics for Image Segmentation
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.
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Text Reference
Julian Yarkony and Charless C. Fowlkes. Planar ultrametrics for image segmentation. In Neural Information Processing Systems (NIPS). 2015.BibTeX Reference
@inproceedings{YarkonyF_NIPS_2015,author = "Yarkony, Julian and Fowlkes, Charless C.",
title = "Planar Ultrametrics for Image Segmentation",
booktitle = "Neural Information Processing Systems (NIPS)",
year = "2015",
tag = "grouping"
}