VLDB 2026 Research / reviewers in the wild / expert
Gabriel Cantareiro
dblp:85/10397
· 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 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Visualization and visual analytics › graph visualization
edge bundling |
0.1 | 1 | 2011 | Skeleton-Based Edge Bundling for Graph Visualization · IEEE Trans. Vis. Comput. Graph. 2011 |
Visualization and visual analytics
graph visualization |
0.1 | 1 | 2011 | Skeleton-Based Edge Bundling for Graph Visualization · IEEE Trans. Vis. Comput. Graph. 2011 |
Visualization and visual analytics › multivariate data visualization
pixel-based visualization |
0.0 | 1 | 2011 | Skeleton-Based Edge Bundling for Graph Visualization · IEEE Trans. Vis. Comput. Graph. 2011 |
Visualization and visual analytics
visual analytics |
0.0 | 1 | 2011 | Skeleton-Based Edge Bundling for Graph Visualization · IEEE Trans. Vis. Comput. Graph. 2011 |
Methods — techniques the papers use, named apart from their topics
edge clustering · 0.1distance field · 0.12d skeletonization · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2011 | Skeleton-Based Edge Bundling for Graph VisualizationabstractIn this paper, we present a novel approach for constructing bundled layouts of general graphs. As layout cues for bundles, we use medial axes, or skeletons, of edges which are similar in terms of position information. We combine edge clustering, distance fields, and 2D skeletonization to construct progressively bundled layouts for general graphs by iteratively attracting edges towards the centerlines of level sets of their distance fields. Apart from clustering, our entire pipeline is image-based with an efficient implementation in graphics hardware. Besides speed and implementation simplicity, our method allows explicit control of the emphasis on structure of the bundled layout, i.e. the creation of strongly branching (organic-like) or smooth bundles. We demonstrate our method on several large real-world graphs. Ozan Ersoy, Christophe Hurter, Fernando Vieira Paulovich, Gabriel Cantareiro, Alexandru C. Telea |
IEEE Trans. Vis. Comput. Graph. | 4 |