Local Reflectional Symmetry Detection in Point Clouds Using a Simple PCA-Based Shape Descriptor
The result's identifiers
Result code in 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>
Result on the web
<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>
Alternative languages
Result language
angličtina
Original language name
Local Reflectional Symmetry Detection in Point Clouds Using a Simple PCA-Based Shape Descriptor
Original language description
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.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GF21-08009K" target="_blank" >GF21-08009K: Generalized Symmetries and Equivalences of Geometric Data</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
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
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e-ISSN
2184-4321
Number of pages
12
Pages from-to
52-63
Publisher name
Scitipress digital library
Place of publication
Setúbal
Event location
Lisabon, Portugalsko
Event date
Feb 19, 2023
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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