Edit Distances for Comparing Merge Trees
IEEE Conference on Visualization, 2017
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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To cite: Raghavendra Sridharamurthy, Adhitya Kamakshidasan and Vijay Natarajan. "Edit Distances for Comparing Merge Trees" Proc. IEEE Conference on Visualization (Posters), 2017
BibTeX:
@inproceedings{SridharamurthyVis2017, title={{Edit Distances for Comparing Merge Trees}}, author={Sridharamurthy, Raghavendra and Kamakshidasan, Adhitya and Natarajan, Vijay}, booktitle={IEEE SciVis Posters}, year={2017} } Best Poster Award IEEE Conference on Visualization, SciVis Track, 2017
Poster