Feature Surfaces in Symmetric Tensor Fields Based on Eigenvalue Manifold
- Submitting institution
-
University of Nottingham, The
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 4571415
- Type
- D - Journal article
- DOI
-
10.1109/tvcg.2015.2484343
- Title of journal
- IEEE Transactions on Visualization and Computer Graphics
- Article number
- -
- First page
- 1248
- Volume
- 22
- Issue
- 3
- ISSN
- 1077-2626
- Open access status
- Out of scope for open access requirements
- Month of publication
- March
- Year of publication
- 2016
- 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
-
7
- Research group(s)
-
-
- Citation count
- 9
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This work advances the state-of-the-art in feature extraction from three-dimensional tensor fields by extracting and visualizing a new class of topology-based surfaces. The work is significant because it enables a novel set of surface-type features in 3D tensor fields to be detected, studied, and analysed making them visible for the first time. The surfaces partition the 3D tensor field into regions of similar behaviour, thus, new understanding of the fields can be obtained. This type of analysis has many applications in both solid and fluid mechanics.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
