IEEE VIS 2024 Content: Curve Segment Neighborhood-based Vector Field Exploration

Curve Segment Neighborhood-based Vector Field Exploration

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Nguyen K Phan - University of Houston, Houston, United States

 Guoning Chen - University of Houston, Houston, United States

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 Room: Bayshore VI

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2024-10-18T13:30:00Z

Exemplar figure, described by caption below — A visualization of the (1) 3D streamlines dataset of the Solar Plume dataset on the left side, color-coded by their respective communities and (2) the community force-directed graph created using Louvain community detection at resolution = 0.7 on the right side.

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Keywords

Vector field, neighbor search, community detection

Abstract

Integral curves have been widely used to represent and analyze various vector fields. In this paper, we propose a Curve Segment Neighborhood Graph (CSNG) to capture the relationships between neighboring curve segments. This graph representation enables us to adapt the fast community detection algorithm, i.e., the Louvain algorithm, to identify individual graph communities from CSNG. Our results show that these communities often correspond to the features of the flow. To achieve a multi-level interactive exploration of the detected communities, we adapt a force-directed layout that allows users to refine and re-group communities based on their domain knowledge. We incorporate the proposed techniques into an interactive system to enable effective analysis and interpretation of complex patterns in large-scale integral curve datasets.