Details
| Original language | English |
|---|---|
| Title of host publication | International Archives of the Photogrammetry, Remote Sensing und Spatial Information Sciences |
| Subtitle of host publication | XXIV ISPRS Congress (2021 edition) |
| Publisher | Copernicus Publications |
| Pages | 277-282 |
| Number of pages | 6 |
| Publication status | Published - 28 Jun 2021 |
Publication series
| Name | International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives |
|---|---|
| Publisher | International Society for Photogrammetry and Remote Sensing |
| ISSN (Print) | 1682-1750 |
Abstract
Keywords
- 3D Quality Map, Building Modelling, Incremental Refinement, LiDAR, Mobile Mapping, Point Cloud
ASJC Scopus subject areas
- Social Sciences(all)
- Geography, Planning and Development
- Computer Science(all)
- Information Systems
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International Archives of the Photogrammetry, Remote Sensing und Spatial Information Sciences: XXIV ISPRS Congress (2021 edition). Copernicus Publications, 2021. p. 277-282 (International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Incremental map refinement of building information using lidar point clouds
AU - Zou, Qianqian
AU - Sester, Monika
N1 - Funding Information: This work was funded by the German Research Foundation (DFG) as a part of the Research Training Group GRK2159, “Integrity and collaboration in dynamic sensor networks” (i.c.sens).
PY - 2021/6/28
Y1 - 2021/6/28
N2 - For autonomous systems, an accurate and precise map of the environment is of importance. Mapping from LiDAR point clouds is one of the promising ways to generate 3D environment models. However, there are many problems caused by inaccurate data, missing areas, low density of points and sensor noise. Also, it is often not possible or accurate enough to generate a map from only one measurement campaign. In this paper, we propose a method to incrementally refine the map by several measurements from different campaigns and represent the map in a hierarchical way with a measure indicating uncertainty and the level of detail for objects. The idea is thus to store all captured information with a tentative semantics and uncertainty – even when it is not yet complete. Hence, occulated areas are presented as well, which can be possibly improved by the supplemental observation from the next measurement campaign. The proposed 3D environment model framework and the incremental update method are evaluated using LiDAR scans obtained from Riegl Mobile Mapping System.
AB - For autonomous systems, an accurate and precise map of the environment is of importance. Mapping from LiDAR point clouds is one of the promising ways to generate 3D environment models. However, there are many problems caused by inaccurate data, missing areas, low density of points and sensor noise. Also, it is often not possible or accurate enough to generate a map from only one measurement campaign. In this paper, we propose a method to incrementally refine the map by several measurements from different campaigns and represent the map in a hierarchical way with a measure indicating uncertainty and the level of detail for objects. The idea is thus to store all captured information with a tentative semantics and uncertainty – even when it is not yet complete. Hence, occulated areas are presented as well, which can be possibly improved by the supplemental observation from the next measurement campaign. The proposed 3D environment model framework and the incremental update method are evaluated using LiDAR scans obtained from Riegl Mobile Mapping System.
KW - 3D Quality Map
KW - Building Modelling
KW - Incremental Refinement
KW - LiDAR
KW - Mobile Mapping
KW - Point Cloud
UR - http://www.scopus.com/inward/record.url?scp=85116050542&partnerID=8YFLogxK
U2 - 10.5194/isprs-archives-xliii-b2-2021-277-2021
DO - 10.5194/isprs-archives-xliii-b2-2021-277-2021
M3 - Conference contribution
T3 - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
SP - 277
EP - 282
BT - International Archives of the Photogrammetry, Remote Sensing und Spatial Information Sciences
PB - Copernicus Publications
ER -