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Henriette Lipschütz

dblp:290/5553 · DBLP profile ↗
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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

TopicWeightPapersLastEvidence papers
Geometric modeling and processing
mesh generation
1.012026
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
1.012026
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
0.312026
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
0.312026
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
0.312026
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
0.312026
Feature-aware manifold meshing and remeshing of point clouds and polyhedral surfaces with guaranteed smallest edge length · Comput. Aided Des. 2026
YearPublicationVenuePosition
2026 Feature-aware manifold meshing and remeshing of point clouds and polyhedral surfaces with guaranteed smallest edge length
abstract
Point 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