Efficient RANSAC for Point-Cloud Shape Detection

In this paper we present an automatic algorithm to detect basic shapes in unorganized point clouds. The algorithm decomposes the point cloud into a concise, hybrid structure of inherent shapes and a set of remaining points. Each detected shape serves as a proxy for a set of corresponding points. Our...

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Veröffentlicht in:Computer graphics forum Jg. 26; H. 2; S. 214 - 226
Hauptverfasser: Schnabel, R., Wahl, R., Klein, R.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Oxford, UK Blackwell Publishing Ltd 01.06.2007
Schlagworte:
Algorithms
Construction
Engineering
geometry analysis
I.3.5: Computational Geometry and Object Modeling Curve
I.4.8: Scene Analysis Shape
I.4.8: Scene Analysis Shape; Surface Fitting
large point-clouds
localized RANSAC
object representations
primitive shapes
shape fitting
solid
Studies
surface
Surface Fitting
Ventilation
ISSN:0167-7055, 1467-8659
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Zusammenfassung:In this paper we present an automatic algorithm to detect basic shapes in unorganized point clouds. The algorithm decomposes the point cloud into a concise, hybrid structure of inherent shapes and a set of remaining points. Each detected shape serves as a proxy for a set of corresponding points. Our method is based on random sampling and detects planes, spheres, cylinders, cones and tori. For models with surfaces composed of these basic shapes only, for example, CAD models, we automatically obtain a representation solely consisting of shape proxies. We demonstrate that the algorithm is robust even in the presence of many outliers and a high degree of noise. The proposed method scales well with respect to the size of the input point cloud and the number and size of the shapes within the data. Even point sets with several millions of samples are robustly decomposed within less than a minute. Moreover, the algorithm is conceptually simple and easy to implement. Application areas include measurement of physical parameters, scan registration, surface compression, hybrid rendering, shape classification, meshing, simplification, approximation and reverse engineering.
Bibliographie:ark:/67375/WNG-QL894LFQ-1
ArticleID:CGF1016
istex:8DBAC1D02BDB138BAAFD0EDA14188D74F9CB1A8F
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ObjectType-Feature-1
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ISSN:0167-7055
1467-8659
DOI:10.1111/j.1467-8659.2007.01016.x