Abstract
Recently, we have lots of LiDAR (light detection and ranging) data, for applications of high-resolution maps including geography, geology, forestry, and others. One of the current research and industrial issues is efficient ways of storing the LiDAR data itself, and also elegant ways of extracting geometric primitives from those LiDAR-scanned 3D point clouds. In this paper, we first analyze the characteristics of LiDAR data and tis storage schemes. Additionally, we present an efficient method to extract geometric primitives from those point clouds. Its implementation and results are also presented.
| Original language | English |
|---|---|
| Pages (from-to) | 741-748 |
| Number of pages | 8 |
| Journal | Cluster Computing |
| Volume | 20 |
| Issue number | 1 |
| DOIs | |
| State | Published - 1 Mar 2017 |
Keywords
- Efficient processing
- Geometric primitive
- LiDAR
- Light detection and ranging
- Point clouds
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