Augmented Postprocessing of the FTLS Vectorization Algorithm

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F16%3APU119785" target="_blank" >RIV/00216305:26220/16:PU119785 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.5220/0005962902160223" target="_blank" >http://dx.doi.org/10.5220/0005962902160223</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.5220/0005962902160223" target="_blank" >10.5220/0005962902160223</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Augmented Postprocessing of the FTLS Vectorization Algorithm

Popis výsledku v původním jazyce

Vectorization is a widely used technique in many areas, mainly in robotics and image processing. Applications in these domains frequently require both speed (for real-time operation) and accuracy (for maximal information gain). This paper proposes an optimization for the high speed vectorization methods, which leads to nearly optimal results. The FTLS algorithm uses the total least squares method for fitting the lines into the point cloud and the presented augmentation for the refinement of the results, is based on a modified Nelder-Mead method. As shown on several experiments, this approach leads to better utilization of the information contained in the point cloud. As a result, the quality of approximation grows steadily with the number of points being vectorized, which was not achieved before. Performance costs are still comparable to the original algorithm, so the real-time operation is not endangered.

Název v anglickém jazyce

Augmented Postprocessing of the FTLS Vectorization Algorithm

Popis výsledku anglicky

Vectorization is a widely used technique in many areas, mainly in robotics and image processing. Applications in these domains frequently require both speed (for real-time operation) and accuracy (for maximal information gain). This paper proposes an optimization for the high speed vectorization methods, which leads to nearly optimal results. The FTLS algorithm uses the total least squares method for fitting the lines into the point cloud and the presented augmentation for the refinement of the results, is based on a modified Nelder-Mead method. As shown on several experiments, this approach leads to better utilization of the information contained in the point cloud. As a result, the quality of approximation grows steadily with the number of points being vectorized, which was not achieved before. Performance costs are still comparable to the original algorithm, so the real-time operation is not endangered.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20201 - Electrical and electronic engineering

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2016

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2016) - Volume 2

ISBN

978-989-758-198-4

ISSN

—

e-ISSN

—

Počet stran výsledku

8

Strana od-do

216-223

Název nakladatele

Neuveden

Místo vydání

Lisabon

Místo konání akce

Lisabon

Datum konání akce

29. 7. 2016

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000392601900022