Name
Title | ||
|---|---|---|
Fast Filtering of LiDAR Point Cloud in Urban Areas Based on Scan Line Segmentation and GPU Acceleration |
Abstract | ||
|---|---|---|
The fast filtering of massive point cloud data from light detection and ranging (LiDAR) systems is important for many applications, such as the automatic extraction of digital elevation models in urban areas. We propose a simple scan-line-based algorithm that detects local lowest points first and treats them as the seeds to grow into ground segments by using slope and elevation. The scan line segmentation algorithm can be naturally accelerated by parallel computing due to the independent processing of each line. Furthermore, modern graphics processing units (GPUs) can be used to speed up the parallel process significantly. Using a strip of a LiDAR point cloud, with up to 48 million points, we test the algorithm in terms of both error rate and time performance. The tests show that the method can produce satisfactory results in less than 0.6 s of processing time using the GPU acceleration. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/LGRS.2012.2205130 | IEEE Geosci. Remote Sensing Lett. |
Keywords | Field | DocType |
parallel processing,graphics processing unit,acceleration,light detection and ranging (lidar),digital elevation model,scan line,segmentation,graphics processing units,gpu acceleration,graphics processing unit (gpu),automatic extraction,digital elevation models,point detection,optical radar,radar detection,geophysical signal processing,scan line segmentation algorithm,filtering theory,light detection and ranging system,parallel computing,fast filtering,lidar point cloud filtering,remote sensing,instruction sets,prediction algorithms,laser radar | Computer vision,Computer science,Segmentation,Remote sensing,Filter (signal processing),Digital elevation model,Lidar,Artificial intelligence,Graphics processing unit,Point cloud,Scan line,Speedup | Journal |
Volume | Issue | ISSN |
10 | 2 | 1545-598X |
Citations | PageRank | References |
13 | 0.72 | 6 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiangyun Hu | 1 | 79 | 8.87 |
| Xiaokai Li | 2 | 13 | 0.72 |
| Yongjun Zhang | 3 | 164 | 33.87 |