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Topological Feature Search in Time-Varying Multifield Data

Agarwal, T and Chattopadhyay, A and Natarajan, V (2021) Topological Feature Search in Time-Varying Multifield Data. In: 8th Workshop on Topological Methods in Data Analysis and Visualization, TopoInVis, 17 June - 19 June 2019, Nyköping, pp. 197-217.

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Official URL: https://doi.org/10.1007/978-3-030-83500-2_11


A wide range of data that appear in scientific experiments and simulations are multivariate or multifield in nature, consisting of multiple scalar fields. Topological feature search of such data aims to reveal important properties useful to the domain scientists. It has been shown in recent works that a single scalar field is insufficient to capture many important topological features in the data, instead one needs to consider topological relationships between multiple scalar fields. In the current paper, we propose a novel method of finding similarity between two multifield data by comparing their respective fiber component distributions. Given a time-varying multifield data, the method computes a metric plot for each pair of histograms at consecutive time stamps to understand the topological changes in the data over time. We validate the method using real and synthetic data. The effectiveness of the proposed method is shown by its ability to capture important topological features that are not always possible to detect using the individual component scalar fields.

Item Type: Conference Paper
Publication: Mathematics and Visualization
Publisher: Springer Science and Business Media Deutschland GmbH
Additional Information: The copyright for this article belongs to Springer Science and Business Media Deutschland GmbH.
Keywords: Comparison measure; Distribution; Features; Fiber-component; Multifield topology; Time-varying
Department/Centre: Division of Electrical Sciences > Computer Science & Automation
Date Deposited: 09 Jun 2023 07:00
Last Modified: 09 Jun 2023 07:00
URI: https://eprints.iisc.ac.in/id/eprint/81814

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