TY - JOUR
T1 - Dynamic Nested Tracking Graphs
AU - Lukasczyk, Jonas
AU - Garth, Christoph
AU - Weber, Gunther H.
AU - Biedert, Tim
AU - Maciejewski, Ross
AU - Leitte, Heike
N1 - Funding Information:
This research was funded by the German research foundation (DFG) within the IRTG 2057 “Physical Modeling for Virtual Manufacturing Systems and Processes”. This research was also supported by the Exascale Computing Project (17-SC-20-SC), a collaborative effort of the U.S. Department of Energy Office of Science and the National Nuclear Security Administration.
Publisher Copyright:
© 1995-2012 IEEE.
PY - 2020/1
Y1 - 2020/1
N2 - 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.
AB - 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.
KW - Feature Tracking
KW - Image Databases
KW - Nested Tracking Graphs
KW - Post Hoc Visual Analytics
KW - Topological Data Analysis
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U2 - 10.1109/TVCG.2019.2934368
DO - 10.1109/TVCG.2019.2934368
M3 - Article
C2 - 31581084
AN - SCOPUS:85075636898
SN - 1077-2626
VL - 26
SP - 249
EP - 258
JO - IEEE Transactions on Visualization and Computer Graphics
JF - IEEE Transactions on Visualization and Computer Graphics
IS - 1
M1 - 8854335
ER -