Matches in SemOpenAlex for { <https://semopenalex.org/work/W2019418611> ?p ?o ?g. }
Showing items 1 to 69 of
69
with 100 items per page.
- W2019418611 abstract "In the last decade, a great deal of work has been devoted to the elaboration of a sampling theory for smooth surfaces. The goal was to ensure a good reconstruction of a given surface S from a finite subset E of S. The sampling conditions proposed so far offer guarantees provided that E is sufficiently dense with respect to the local feature size of S, which can be true only if S is smooth since the local feature size vanishes at singular points.In this paper, we introduce a new measurable quantity, called the Lipschitz radius, which plays a role similar to that of the local feature size in the smooth setting, but which is well-defined and positive on a much larger class of shapes. Specifically, it characterizes the class of Lipschitz surfaces, which includes in particular all piecewise smooth surfaces such that the normal deviation is not too large around singular points.Our main result is that, if S is a Lipschitz surface and E is a sample of S such that any point of S is at distance less than a fraction of the Lipschitz radius of S, then we obtain similar guarantees as in the smooth setting. More precisely, we show that the Delaunay triangulation of E restricted to S is a 2-manifold isotopic to S lying at bounded Hausdorff distance from S, provided that its facets are not too skinny.We further extend this result to the case of loose samples. As an application, the Delaunay refinement algorithm we proved correct for smooth surfaces works as well and comes with similar guarantees when applied to Lipschitz surfaces." @default.
- W2019418611 created "2016-06-24" @default.
- W2019418611 creator A5032839569 @default.
- W2019418611 creator A5034088489 @default.
- W2019418611 date "2006-06-05" @default.
- W2019418611 modified "2023-10-17" @default.
- W2019418611 title "Provably good sampling and meshing of Lipschitz surfaces" @default.
- W2019418611 cites W1484996622 @default.
- W2019418611 cites W1551360398 @default.
- W2019418611 cites W1969549682 @default.
- W2019418611 cites W2020428772 @default.
- W2019418611 cites W2021369132 @default.
- W2019418611 cites W2029041800 @default.
- W2019418611 cites W2039081484 @default.
- W2019418611 cites W2046305987 @default.
- W2019418611 cites W2089005118 @default.
- W2019418611 cites W2095755994 @default.
- W2019418611 cites W2106209520 @default.
- W2019418611 cites W2115920764 @default.
- W2019418611 cites W2965233088 @default.
- W2019418611 cites W4232449688 @default.
- W2019418611 cites W4235840289 @default.
- W2019418611 cites W4292159986 @default.
- W2019418611 doi "https://doi.org/10.1145/1137856.1137906" @default.
- W2019418611 hasPublicationYear "2006" @default.
- W2019418611 type Work @default.
- W2019418611 sameAs 2019418611 @default.
- W2019418611 citedByCount "50" @default.
- W2019418611 countsByYear W20194186112012 @default.
- W2019418611 countsByYear W20194186112013 @default.
- W2019418611 countsByYear W20194186112014 @default.
- W2019418611 countsByYear W20194186112016 @default.
- W2019418611 countsByYear W20194186112018 @default.
- W2019418611 crossrefType "proceedings-article" @default.
- W2019418611 hasAuthorship W2019418611A5032839569 @default.
- W2019418611 hasAuthorship W2019418611A5034088489 @default.
- W2019418611 hasConcept C106131492 @default.
- W2019418611 hasConcept C121684516 @default.
- W2019418611 hasConcept C134306372 @default.
- W2019418611 hasConcept C140779682 @default.
- W2019418611 hasConcept C22324862 @default.
- W2019418611 hasConcept C31972630 @default.
- W2019418611 hasConcept C33923547 @default.
- W2019418611 hasConcept C41008148 @default.
- W2019418611 hasConceptScore W2019418611C106131492 @default.
- W2019418611 hasConceptScore W2019418611C121684516 @default.
- W2019418611 hasConceptScore W2019418611C134306372 @default.
- W2019418611 hasConceptScore W2019418611C140779682 @default.
- W2019418611 hasConceptScore W2019418611C22324862 @default.
- W2019418611 hasConceptScore W2019418611C31972630 @default.
- W2019418611 hasConceptScore W2019418611C33923547 @default.
- W2019418611 hasConceptScore W2019418611C41008148 @default.
- W2019418611 hasLocation W20194186111 @default.
- W2019418611 hasOpenAccess W2019418611 @default.
- W2019418611 hasPrimaryLocation W20194186111 @default.
- W2019418611 hasRelatedWork W1502031429 @default.
- W2019418611 hasRelatedWork W1994157709 @default.
- W2019418611 hasRelatedWork W2397777611 @default.
- W2019418611 hasRelatedWork W2417585376 @default.
- W2019418611 hasRelatedWork W2748952813 @default.
- W2019418611 hasRelatedWork W2899084033 @default.
- W2019418611 hasRelatedWork W2911623553 @default.
- W2019418611 hasRelatedWork W3185235544 @default.
- W2019418611 hasRelatedWork W4246418678 @default.
- W2019418611 hasRelatedWork W4297791327 @default.
- W2019418611 isParatext "false" @default.
- W2019418611 isRetracted "false" @default.
- W2019418611 magId "2019418611" @default.
- W2019418611 workType "article" @default.