Local Reflectional Symmetry Detection in Point Clouds Using a Simple PCA-Based Shape Descriptor

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F23%3A43968408" target="_blank" >RIV/49777513:23520/23:43968408 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.scitepress.org/Papers/2023/116222/116222.pdf" target="_blank" >https://www.scitepress.org/Papers/2023/116222/116222.pdf</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.5220/0011622200003417" target="_blank" >10.5220/0011622200003417</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Local Reflectional Symmetry Detection in Point Clouds Using a Simple PCA-Based Shape Descriptor

Popis výsledku v původním jazyce

Symmetry is a commonly occurring feature in real world objects and its knowledge can be useful in various applications. Different types of symmetries exist but we only consider the reflectional symmetry which is probably the most common one. Multiple methods exist that aim to find the global reflectional symmetry of a given 3D object and although this task on its own is not easy, finding symmetries of objects that are merely parts of larger scenes is much more difficult. Such symmetries are often called local symmetries and they commonly occur in real world 3D scans of whole scenes or larger areas. In this paper we propose a simple PCA-based local shape descriptor that can be easily used for potential symmetric point matching in 3D point clouds and, building on previous work, we present a new method for detecting local reflectional symmetries in 3D point clouds which combines the PCA descriptor point matching with the density peak location algorithm. We show the results of our method for several real 3D scanned scenes and demonstrate its computational efficiency and robustness to noise.

Název v anglickém jazyce

Local Reflectional Symmetry Detection in Point Clouds Using a Simple PCA-Based Shape Descriptor

Popis výsledku anglicky

Symmetry is a commonly occurring feature in real world objects and its knowledge can be useful in various applications. Different types of symmetries exist but we only consider the reflectional symmetry which is probably the most common one. Multiple methods exist that aim to find the global reflectional symmetry of a given 3D object and although this task on its own is not easy, finding symmetries of objects that are merely parts of larger scenes is much more difficult. Such symmetries are often called local symmetries and they commonly occur in real world 3D scans of whole scenes or larger areas. In this paper we propose a simple PCA-based local shape descriptor that can be easily used for potential symmetric point matching in 3D point clouds and, building on previous work, we present a new method for detecting local reflectional symmetries in 3D point clouds which combines the PCA descriptor point matching with the density peak location algorithm. We show the results of our method for several real 3D scanned scenes and demonstrate its computational efficiency and robustness to noise.

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/GF21-08009K" target="_blank" >GF21-08009K: Zobecněné symetrie a ekvivalence geometrických dat</a><br>

Návaznosti

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

Rok uplatnění

2023

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - GRAPP

ISBN

978-989-758-634-7

ISSN

—

e-ISSN

2184-4321

Počet stran výsledku

12

Strana od-do

52-63

Název nakladatele

Scitipress digital library

Místo vydání

Setúbal

Místo konání akce

Lisabon, Portugalsko

Datum konání akce

19. 2. 2023

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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