期刊
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
卷 26, 期 1, 页码 249-258出版社
IEEE COMPUTER SOC
DOI: 10.1109/TVCG.2019.2934368
关键词
Topological Data Analysis; Nested Tracking Graphs; Image Databases; Feature Tracking; Post Hoc Visual Analytics
资金
- German research foundation (DFG) [IRTG 2057]
- Exascale Computing Project [17-SC-20-SC]
This work describes an approach for the interactive visual analysis of large-scale simulations, where numerous superlevel set components and their evolution are of primary interest. The approach first derives, at simulation runtime, a specialized Cinema database that consists of images of component groups, and topological abstractions. This database is processed by a novel graph operation-based nested tracking graph algorithm (GO-NTG) that dynamically computes NTGs for component groups based on size, overlap, persistence, and level thresholds. The resulting NTGs are in turn used in a feature-centered visual analytics framework to query specific database elements and update feature parameters, facilitating flexible post hoc analysis.
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