Abstract
We show that reconstructing a curve in R d for d = 2 from a 0.66-sample is always possible using an algorithm similar to the classical NN-Crust algorithm. Previously, this was only known to be possible for 0.47-samples in R 2 and 1 3 -samples in R d for d = 3. In addition, we show that there is not always a unique way to reconstruct a curve from a 0.72-sample; this was previously only known for 1-samples. We also extend this non-uniqueness result to hypersurfaces in all higher dimensions.
Originalsprache | englisch |
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Titel | 38th International Symposium on Computational Geometry (SoCG 2022) |
Redakteure/-innen | Xavier Goaoc, Michael Kerber |
Herausgeber (Verlag) | Schloss Dagstuhl - Leibniz-Zentrum für Informatik |
Seiten | 9:1-9:17 |
ISBN (elektronisch) | 978-3-95977-227-3 |
DOIs | |
Publikationsstatus | Veröffentlicht - 1 Juni 2022 |
Veranstaltung | 38th International Symposium on Computational Geometry: SoCG 2022 - Berlin, Germany, Berlin, Deutschland Dauer: 7 Juni 2022 → 10 Juni 2022 https://www.inf.fu-berlin.de/inst/ag-ti/socg22/socg.html |
Publikationsreihe
Name | Leibniz International Proceedings in Informatics, LIPIcs |
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Band | 224 |
ISSN (Print) | 1868-8969 |
Konferenz
Konferenz | 38th International Symposium on Computational Geometry |
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Kurztitel | SoCG 2022 |
Land/Gebiet | Deutschland |
Ort | Berlin |
Zeitraum | 7/06/22 → 10/06/22 |
Internetadresse |
ASJC Scopus subject areas
- Software
Fields of Expertise
- Information, Communication & Computing