Name
Title | ||
|---|---|---|
Out-of-Core Surface Reconstruction from Large Point Sets for Infrastructure Inspection |
Abstract | ||
|---|---|---|
This paper presents a simple, effective, yet fast out-of-core method for surface reconstruction based on the vector field surface representation. The algorithm is designed to handle massive amount of real-world point clouds representing large infrastructures (e.g. underwater hydroelectric structure) acquired by LiDAR, sonar or laser scanning system using out-of-core techniques. Our method allows performing seamless surface reconstruction from unorganized, unrented, non-uniform and highly noisy data that include outliers. The applicability of the method has been evaluated in the context of hydroelectric infrastructure inspection, and its performance has been tested using synthetically produced data and field data captured on different Hydro-Quebec's sites by laser line scanning, LiDAR and sonar measurement systems. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/CRV.2015.48 | CRV |
Keywords | Field | DocType |
Surface reconstruction, vector field, out-of-core processing, large point cloud | Iterative reconstruction,Computer vision,Surface reconstruction,Laser scanning,Computer science,Sonar,Out-of-core algorithm,Lidar,Artificial intelligence,Point cloud,Underwater | Conference |
Citations | PageRank | References |
0 | 0.34 | 23 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chen Xu | 1 | 0 | 0.34 |
| Simon Frechet | 2 | 0 | 0.34 |
| Denis Laurendeau | 3 | 803 | 169.72 |
| François Mirallès | 4 | 2 | 0.74 |