Abstract
In this paper, we propose a method for panoramic point-cloud rendering-based polygon extraction from indoor mobile LiDAR data. Our aim was to improve region-based point-cloud clustering in modeling after point-cloud registration. First, we propose a point-cloud clustering methodology for polygon extraction on a panoramic range image generated with point-based rendering from a massive point cloud. Next, we describe an experiment that was conducted to verify our methodology with an indoor mobile mapping system in an indoor environment. This experiment was wall-surface extraction using a rendered point-cloud from 64 viewpoints over a wide indoor area. Finally, we confirmed that our proposed methodology could achieve polygon extraction through point-cloud clustering from a complex indoor environment.
| Original language | English |
|---|---|
| Pages (from-to) | 181-186 |
| Number of pages | 6 |
| Journal | International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives |
| Volume | 40 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 2014 |
| Event | ISPRS Technical Commission IV Symposium 2014 - Suzhou, China Duration: 2014 May 14 → 2014 May 16 |
Keywords
- 3D polygon extraction
- Indoor mobile mapping
- Point cloud clustering
- Point-based rendering
- Point-cloud
ASJC Scopus subject areas
- Information Systems
- Geography, Planning and Development