Demo Data from EDBT 2026 / reviewers in the wild / expert
Henriette Lipschütz
dblp:290/5553
· DBLP profile ↗
2ranked-venue papers
2as first author
2since 2021 · last 2026
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 2 · 2 first-author · 2 since 2021
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 |
Geometric modeling and processing · 100% |
Topics — the 6 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Geometric modeling and processing
mesh generation |
1.0 | 1 | 2026 | Feature-aware manifold meshing and remeshing of point clouds and polyhedral surfaces with guaranteed smallest edge length · Comput. Aided Des. 2026 |
Geometric modeling and processing › shape representation › mesh representation
triangle mesh |
1.0 | 1 | 2026 | Feature-aware manifold meshing and remeshing of point clouds and polyhedral surfaces with guaranteed smallest edge length · Comput. Aided Des. 2026 |
Geometric modeling and processing › surface reconstruction
mesh reconstruction |
0.3 | 1 | 2026 | Feature-aware manifold meshing and remeshing of point clouds and polyhedral surfaces with guaranteed smallest edge length · Comput. Aided Des. 2026 |
Geometric modeling and processing › shape representation › point-based representation
point cloud |
0.3 | 1 | 2026 | Feature-aware manifold meshing and remeshing of point clouds and polyhedral surfaces with guaranteed smallest edge length · Comput. Aided Des. 2026 |
Geometric modeling and processing › shape representation › mesh representation
polyhedral surface |
0.3 | 1 | 2026 | Feature-aware manifold meshing and remeshing of point clouds and polyhedral surfaces with guaranteed smallest edge length · Comput. Aided Des. 2026 |
Geometric modeling and processing › mesh processing
remeshing |
0.3 | 1 | 2026 | Feature-aware manifold meshing and remeshing of point clouds and polyhedral surfaces with guaranteed smallest edge length · Comput. Aided Des. 2026 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | Feature-aware manifold meshing and remeshing of point clouds and polyhedral surfaces with guaranteed smallest edge lengthabstractPoint clouds and polygonal meshes are widely used when modeling real-world scenarios. Here, point clouds arise, for instance, from acquisition processes applied in various surroundings, such as reverse engineering, rapid prototyping, or cultural preservation. Based on these raw data, polygonal meshes are created to, for example, run various simulations. For such applications, the utilized meshes must be of high quality. This paper presents an algorithm to derive triangle meshes from unstructured point clouds. The occurring edges have a close to uniform length and their lengths are bounded from below. Theoretical results guarantee the output to be manifold, provided suitable input and parameter choices. Further, the paper presents several experiments establishing that the algorithms can compete with widely used competitors in terms of quality of the output and timing and the output is stable under moderate levels of noise. Additionally, we expand the algorithm to detect and respect features on point clouds as well as to remesh polyhedral surfaces, possibly with features. Supplementary material, an extended preprint, a link to a previously published version of the article, utilized models, and implementation details are made available online . Henriette Lipschütz, Ulrich Reitebuch, Konrad Polthier, Martin Skrodzki |
Comput. Aided Des. | 1 |
| 2021 | Single-sized spheres on surfaces (S4)
Henriette Lipschütz, Martin Skrodzki, Ulrich Reitebuch, Konrad Polthier |
Comput. Aided Geom. Des. | 1 |