Multivariate analysis of curvature estimators

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F17%3A43930520" target="_blank" >RIV/49777513:23520/17:43930520 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1080/16864360.2016.1199756" target="_blank" >http://dx.doi.org/10.1080/16864360.2016.1199756</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1080/16864360.2016.1199756" target="_blank" >10.1080/16864360.2016.1199756</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Multivariate analysis of curvature estimators

Popis výsledku v původním jazyce

Principal curvature is one of the defining features of surfaces studied in differential geometry. While well-defined and easy to evaluate for smooth surfaces, it cannot be evaluated exactly if the surface is represented by a polygon mesh, unless some special conditions apply. Nevertheless, estimating the curvature of a surface mesh is a crucial step in common mesh processing algorithms, such as mesh segmentation, mesh smoothing, remeshing and others. While a wealth of approaches for estimating the curvature has been proposed in the literature, aiming at the best possible precision of the estimation, an objective study identifying the strengths and weaknesses of the different methods was usually lacking. We present results of a comprehensive study focused on different aspects of curvature estimation. We extend some of the estimators in order to match properties of others and thus provide comparable results. The results of the study indicate that currently there is no one universally optimal method of curvature estimation. Choosing an appropriate curvature estimation algorithm is highly application specific, and we provide the guidance required for making such choice

Název v anglickém jazyce

Multivariate analysis of curvature estimators

Popis výsledku anglicky

Principal curvature is one of the defining features of surfaces studied in differential geometry. While well-defined and easy to evaluate for smooth surfaces, it cannot be evaluated exactly if the surface is represented by a polygon mesh, unless some special conditions apply. Nevertheless, estimating the curvature of a surface mesh is a crucial step in common mesh processing algorithms, such as mesh segmentation, mesh smoothing, remeshing and others. While a wealth of approaches for estimating the curvature has been proposed in the literature, aiming at the best possible precision of the estimation, an objective study identifying the strengths and weaknesses of the different methods was usually lacking. We present results of a comprehensive study focused on different aspects of curvature estimation. We extend some of the estimators in order to match properties of others and thus provide comparable results. The results of the study indicate that currently there is no one universally optimal method of curvature estimation. Choosing an appropriate curvature estimation algorithm is highly application specific, and we provide the guidance required for making such choice

Druh

J_SC - Článek v periodiku v databázi SCOPUS

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/LO1506" target="_blank" >LO1506: Podpora udržitelnosti centra NTIS - Nové technologie pro informační společnost</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2017

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Computer-aided design and applications

ISSN

1686-4360

e-ISSN

—

Svazek periodika

14

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

12

Strana od-do

58-69

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-84975321393