Demo Data from EDBT 2026 / reviewers in the wild / expert
Paul Vincent
dblp:24/7505
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2011
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer graphics and multimedia
1 paper |
Visualization and visual analytics · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Visualization and visual analytics
flow visualization |
0.1 | 1 | 2011 | Asymmetric Tensor Field Visualization for Surfaces · IEEE Trans. Vis. Comput. Graph. 2011 |
Visualization and visual analytics
scientific visualization |
0.1 | 1 | 2011 | Asymmetric Tensor Field Visualization for Surfaces · IEEE Trans. Vis. Comput. Graph. 2011 |
Visualization and visual analytics › scientific visualization
tensor field visualization |
0.1 | 1 | 2011 | Asymmetric Tensor Field Visualization for Surfaces · IEEE Trans. Vis. Comput. Graph. 2011 |
Methods — techniques the papers use, named apart from their topics
image-space rendering · 0.1elliptical glyphs · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2011 | Asymmetric Tensor Field Visualization for SurfacesabstractAsymmetric tensor field visualization can provide important insight into fluid flows and solid deformations. Existing techniques for asymmetric tensor fields focus on the analysis, and simply use evenly-spaced hyperstreamlines on surfaces following eigenvectors and dual-eigenvectors in the tensor field. In this paper, we describe a hybrid visualization technique in which hyperstreamlines and elliptical glyphs are used in real and complex domains, respectively. This enables a more faithful representation of flow behaviors inside complex domains. In addition, we encode tensor magnitude, an important quantity in tensor field analysis, using the density of hyperstreamlines and sizes of glyphs. This allows colors to be used to encode other important tensor quantities. To facilitate quick visual exploration of the data from different viewpoints and at different resolutions, we employ an efficient image-space approach in which hyperstreamlines and glyphs are generated quickly in the image plane. The combination of these techniques leads to an efficient tensor field visualization system for domain scientists. We demonstrate the effectiveness of our visualization technique through applications to complex simulated engine fluid flow and earthquake deformation data. Feedback from domain expert scientists, who are also co-authors, is provided. Darrel Palke, Zhongzang Lin, Guoning Chen, Harry Yeh, Paul Vincent, Robert S. Laramee, Eugene Zhang |
IEEE Trans. Vis. Comput. Graph. | 5 |