Reconstruction of Corrupted Vector Fields using Radial Basis Functions

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F19%3A43957985" target="_blank" >RIV/49777513:23520/19:43957985 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1109/Informatics47936.2019.9119297" target="_blank" >http://dx.doi.org/10.1109/Informatics47936.2019.9119297</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/Informatics47936.2019.9119297" target="_blank" >10.1109/Informatics47936.2019.9119297</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Reconstruction of Corrupted Vector Fields using Radial Basis Functions

Popis výsledku v původním jazyce

The vector fields may be results from the measurements of real flow experiments. However, during the measurements, some parts of the vector field can be measured incorrectly or even some parts of the vector field are not possible to capture due to some shading and invisibility. In this paper, we focus on the reconstruction of such corrupted vector fields. We detect the locations, where the vector field was measured incorrectly and reconstruct those locations of the vector field. For the reconstruction, we use Radial Basis Functions (RBF) approximation to fill the missing locations of the vector field as well as to correct and smooth the locations of the vector field, where it was probably measured with some error. The results of the proposed method are presented in this paper.

Název v anglickém jazyce

Reconstruction of Corrupted Vector Fields using Radial Basis Functions

Popis výsledku anglicky

The vector fields may be results from the measurements of real flow experiments. However, during the measurements, some parts of the vector field can be measured incorrectly or even some parts of the vector field are not possible to capture due to some shading and invisibility. In this paper, we focus on the reconstruction of such corrupted vector fields. We detect the locations, where the vector field was measured incorrectly and reconstruct those locations of the vector field. For the reconstruction, we use Radial Basis Functions (RBF) approximation to fill the missing locations of the vector field as well as to correct and smooth the locations of the vector field, where it was probably measured with some error. The results of the proposed method are presented in this paper.

Druh

D - Stať ve sborníku

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/GA17-05534S" target="_blank" >GA17-05534S: Meshless metody pro vizualizaci velkých časově-prostorových vektorových dat</a><br>

Návaznosti

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

Rok uplatnění

2019

Kód důvěrnosti údajů

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

Název statě ve sborníku

2019 IEEE 15th International Scientific Conference on Informatics

ISBN

978-1-72813-181-8

ISSN

—

e-ISSN

—

Počet stran výsledku

6

Strana od-do

363-368

Název nakladatele

IEEE

Místo vydání

Piscataway

Místo konání akce

Poprad

Datum konání akce

20. 11. 2019

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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