Curvature estimation is very popular in geometry processing for the analysis of local surface variations. Despite the large number of methods, no quantitative nor qualitative studies have been conducted for a comparative analysis of the different algorithms on surfaces with small geometric variations, such as chiselled or relief surfaces. In this work we compare eight curvature estimation methods that are commonly adopted by the computer graphics community on a number of triangle meshes derived from scans of surfaces with local reliefs.

A preliminary analysis of methods for curvature estimation on surfaces with local reliefs

E Moscoso Thompson;S Biasotti
2019

Abstract

Curvature estimation is very popular in geometry processing for the analysis of local surface variations. Despite the large number of methods, no quantitative nor qualitative studies have been conducted for a comparative analysis of the different algorithms on surfaces with small geometric variations, such as chiselled or relief surfaces. In this work we compare eight curvature estimation methods that are commonly adopted by the computer graphics community on a number of triangle meshes derived from scans of surfaces with local reliefs.
2019
Istituto di Matematica Applicata e Tecnologie Informatiche - IMATI -
Inglese
P. Cignoni and E. Miguel
EUROGRAPHICS 2019
The European Association for Computer Graphics 40th Annual Conference - EUROGRAPHICS 2019
25
28
https://diglib.eg.org/handle/10.2312/3dor20191056
The Eurographics Association
Goslar
GERMANIA
Sì, ma tipo non specificato
6 - 10 May, 2019
Genova, Italy
Computing methodologies: Shape modeling; Shape analysis;
2
reserved
MOSCOSO THOMPSON, Elia; Biasotti, S
273
info:eu-repo/semantics/conferenceObject
04 Contributo in convegno::04.01 Contributo in Atti di convegno
File in questo prodotto:
File Dimensione Formato  
prod_403326-doc_140382.pdf

non disponibili

Descrizione: A preliminary analysis of methods for curvature estimation on surfaces with local reliefs
Tipologia: Versione Editoriale (PDF)
Dimensione 12.3 MB
Formato Adobe PDF
12.3 MB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/367317
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact