Planar Ultrametrics for Image SegmentationPlanar Ultrametrics for Image SegmentationYarkony, Julian and Fowlkes, Charless C.2015
Paper summarynipsreviewsThe paper presents a method to obtain a hierarchical clustering of a planar graph by posing the problem as that of approximating a set of edge weights using an ultrametric. This is accomplished by minimizing the $\ell_2$ norm between the given edge weights and the learnt ultrametric. Learning the ultrametric amounts to estimating a collection of multicuts that satisfies a hierarchical partitioning constraint. An efficient algorithm is presented that solves an approximation based on a finding a linear combination of a subset of possible two-way cuts of the graph.
The paper presents a method to obtain a hierarchical clustering of a planar graph by posing the problem as that of approximating a set of edge weights using an ultrametric. This is accomplished by minimizing the $\ell_2$ norm between the given edge weights and the learnt ultrametric. Learning the ultrametric amounts to estimating a collection of multicuts that satisfies a hierarchical partitioning constraint. An efficient algorithm is presented that solves an approximation based on a finding a linear combination of a subset of possible two-way cuts of the graph.