Surface Reconstruction from Large Point Clouds Using Virtual Shared Memory Manager

2006 ◽  
pp. 71-80
Author(s):  
Josef Kohout ◽  
Michal Varnuška ◽  
Ivana Kolingerová
Keyword(s):  
Shared Memory ◽  
Surface Reconstruction ◽  
Point Clouds ◽  
Virtual Shared Memory

scholarly journals Computational Geometry-Based Surface Reconstruction for Volume Estimation: A Case Study on Magnitude-Frequency Relations for a LiDAR-Derived Rockfall Inventory

2021 ◽  
Vol 10 (3) ◽  
pp. 157
Author(s):  
Paul-Mark DiFrancesco ◽  
David A. Bonneau ◽  
D. Jean Hutchinson
Keyword(s):  
Computational Geometry ◽  
Surface Reconstruction ◽  
Power Law ◽  
Point Cloud ◽  
Point Clouds ◽  
Volume Estimation ◽  
Estimation Methods ◽  
Small Scale ◽  
Reconstruction Methods ◽  
3D Volume

Key to the quantification of rockfall hazard is an understanding of its magnitude-frequency behaviour. Remote sensing has allowed for the accurate observation of rockfall activity, with methods being developed for digitally assembling the monitored occurrences into a rockfall database. A prevalent challenge is the quantification of rockfall volume, whilst fully considering the 3D information stored in each of the extracted rockfall point clouds. Surface reconstruction is utilized to construct a 3D digital surface representation, allowing for an estimation of the volume of space that a point cloud occupies. Given various point cloud imperfections, it is difficult for methods to generate digital surface representations of rockfall with detailed geometry and correct topology. In this study, we tested four different computational geometry-based surface reconstruction methods on a database comprised of 3668 rockfalls. The database was derived from a 5-year LiDAR monitoring campaign of an active rock slope in interior British Columbia, Canada. Each method resulted in a different magnitude-frequency distribution of rockfall. The implications of 3D volume estimation were demonstrated utilizing surface mesh visualization, cumulative magnitude-frequency plots, power-law fitting, and projected annual frequencies of rockfall occurrence. The 3D volume estimation methods caused a notable shift in the magnitude-frequency relations, while the power-law scaling parameters remained relatively similar. We determined that the optimal 3D volume calculation approach is a hybrid methodology comprised of the Power Crust reconstruction and the Alpha Solid reconstruction. The Alpha Solid approach is to be used on small-scale point clouds, characterized with high curvatures relative to their sampling density, which challenge the Power Crust sampling assumptions.

Research on the Method of Class_A Surface Reconstruction in Automotive Body External Panel Design

2011 ◽  
Vol 291-294 ◽  
pp. 2229-2232
Author(s):  
Ya Bin Cao
Keyword(s):  
Surface Quality ◽  
Surface Reconstruction ◽  
Point Clouds ◽  
Traditional Methods ◽  
Surface Design ◽  
Automotive Body ◽  
Reconstruction Efficiency ◽  
Low Efficiency ◽  
Complicated Surface ◽  
Panel Design

Class_A surface reconstruction is a key part in the design of automotive body external panel. Traditional methods of Class_A surface reconstruction have some disadvantages such as low efficiency, bad flexibility and low surface quality in complicated surface reconstruction. In this paper, a method of Class_A surface reconstruction from point clouds based on NURBS patch was presented, which made surface design more flexible and direct, besides, the reconstruction efficiency and surface quality were improved.

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