Name
Abstract | ||
|---|---|---|
This paper presents an algorithm for segmenting 3D point clouds. It extends terrain elevation models by incorporating two types of representations: (1) ground representations based on averaging the height in the point cloud, (2) object models based on a voxelisation of the point cloud. The approach is deployed on Riegl data (dense 3D laser data) acquired in a campus type of environment and compared against six other terrain models. Amongst elevation models, it is shown to provide the best fit to the data as well as being unique in the sense that it jointly performs ground extraction, overhang representation and 3D segmentation. We experimentally demonstrate that the resulting model is also applicable to path planning. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/IROS.2010.5650541 | Intelligent Robots and Systems |
Keywords | Field | DocType |
image segmentation,mobile robots,path planning,solid modelling,terrain mapping,3D point cloud segmention,3D surface model,hybrid elevation maps,path planning,terrain elevation model | Motion planning,Computer vision,Noise measurement,Segmentation,Computer science,Terrain,Image segmentation,Artificial intelligence,Elevation,Point cloud,Mobile robot | Conference |
ISSN | ISBN | Citations |
2153-0858 | 978-1-4244-6674-0 | 9 |
PageRank | References | Authors |
1.21 | 2 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bertrand Douillard | 1 | 286 | 20.50 |
| James Patrick Underwood | 2 | 442 | 39.37 |
| Melkumyan, N. | 3 | 9 | 1.21 |
| Surya P. N. Singh | 4 | 354 | 29.89 |