Visual Analysis of Spatia-temporal Relations of Pairwise Attributes in Unsteady Flow
- Submitting institution
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Swansea University / Prifysgol Abertawe
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 41185
- Type
- D - Journal article
- DOI
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10.1109/tvcg.2018.2864817
- Title of journal
- IEEE Transactions on Visualization and Computer Graphics
- Article number
- -
- First page
- 1246
- Volume
- 25
- Issue
- 1
- ISSN
- 1077-2626
- Open access status
- Not compliant
- Month of publication
- January
- Year of publication
- 2019
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
-
- Research group(s)
-
-
- Citation count
- 4
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Vector field analysis for unsteady flow is a substantial problem area with multiple applications from understanding climate patterns, ocean transport or mechanical performance. In collaboration with CFD experts, we introduce brand new theory to its study, providing both theoretical and practical guidance on identifying and visualizing the relationships between physical characteristics in time varying spatial flow. New measures and application of mutual information or pairwise attributes allow our more expressive visualisations compared to previous techniques. Our method generalises well and discovers linear and non-linear relationships within the data.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -