Work

Planar Ultrametric Rounding for Image Segmentation

Year: 2015

Type: preprint

Abstract: We study the problem of hierarchical clustering on planar graphs. We formulate this in terms of an LP relaxation of ultrametric rounding. To solve this LP efficiently we introduce a dual cutting plane scheme that uses minimum cost perfect matching as a subroutine in order to efficiently explore the space of planar partitions. We apply our algorithm to the problem of hierarchical image segmentation.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.1507.02407

Authors: Yarkony, Julian, Fowlkes, Charless C.

Institution: University of California, Irvine

Language: English

Topic: Medical Image Segmentation Techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funder: National Science Foundation

Awards: CAREER: Combinatorial Inference and Learning for Fusing Recognition and Perceptual Grouping, Collaborative Research: ABI Innovation: Breaking through the taxonomic barrier of the fossil pollen record using bioimage informatics

OpenAlex ID: W1751619912

Cites: 20

Cited by: 1

Related to: 20