Edit distances for comparing merge trees.

Raghavendra Sridharamurthy, Adhitya Kamakshidasan and Vijay Natarajan.
IEEE SciVis 2017, Poster.
Best Poster Award

Abstract

A merge tree captures the topology of sub-level and super-level sets in a scalar field. Estimating the similarity or dissimilarity between merge trees is an important problem with applications to visualization of time-varying and multi-field data. We present a tree edit distance based approach with a general subtree gap model to compare merge trees. The cost model is based on topological persistence. Experimental results on time-varying data show the utility of the method towards a feature-driven analysis of scalar fields.

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