Name
Abstract | ||
|---|---|---|
This paper presents a systematic study of the scan skewing problem. Scan skewing is the non-rigid deformation of point clouds acquired by LiDAR's and is the result of their sequential scanning nature. We theoretically analyze the impact of skewing on scan matching and subsequently quantify the impact using synthetic LiDAR data with controlled skew distortions. We also show how the Geometric-Algebra LMS, an iterative point set registration filter, can be tuned to incorporate skewing aware weights to reduce the impact of skewing on scan matching. Results with real 3D LiDAR data are also presented. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/IPIN.2016.7743598 | 2016 International Conference on Indoor Positioning and Indoor Navigation (IPIN) |
Keywords | Field | DocType |
LiDAR scan skewing analysis,scan matching,point clouds nonrigid deformation,sequential scanning nature,synthetic LiDAR data,geometric-algebra LMS,iterative point set registration filter | Computer vision,Point set registration,Laser noise,Electronic engineering,Lidar,Artificial intelligence,Skew,Engineering,Lidar data,Point cloud,Distortion,Trajectory | Conference |
ISSN | ISBN | Citations |
2162-7347 | 978-1-5090-2426-1 | 1 |
PageRank | References | Authors |
0.35 | 7 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Anas Al-Nuaimi | 1 | 79 | 6.86 |
| Wilder Bezerra Lopes | 2 | 22 | 2.63 |
| Paul Zeller | 3 | 1 | 0.35 |
| A. Garcea | 4 | 3 | 1.78 |
| Cássio Guimarães Lopes | 5 | 394 | 32.32 |
| Eckehard G. Steinbach | 6 | 2221 | 299.71 |