Details
| Original language | English |
|---|---|
| Pages (from-to) | 583-589 |
| Number of pages | 7 |
| Journal | International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives |
| Volume | 37 |
| Publication status | Published - 2008 |
| Event | 2008 21st ISPRS International Congress for Photogrammetry and Remote Sensing - Beijing, China Duration: 3 Jul 2008 → 11 Jul 2008 |
Abstract
Terrestrial laser scanning provides a three-dimensional sampled representation of the surfaces of terrestrial objects. The fully automatic registration of terrestrial laser scanning point-clouds is still a question as it involves handling huge datasets, irregular point distribution, multiple views, and relatively low textured surfaces. In this paper, we propose a key point based method using intensity and geometry features for the automatic marker-free registration of terrestrial laser scans. We apply the SIFT method for extracting feature points from the reflectance image and geometric constraint for excluding false matches. To evaluate the performance of proposed method, we employ a test scene in downtown Hannover, Germany. Reference orientations were acquired by the standard orientation procedure using retro-reflective targets and manually assisted target selection. In the experiments, we present the results of the proposed method regarding performance, accuracy and running time for the test scene.
Keywords
- Algorithms, Geometry, Laser scanning, Point cloud, Registration, TLS
ASJC Scopus subject areas
- Computer Science(all)
- Information Systems
- Social Sciences(all)
- Geography, Planning and Development
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In: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, Vol. 37, 2008, p. 583-589.
Research output: Contribution to journal › Conference article › Research › peer review
}
TY - JOUR
T1 - Point based registration of terrestrial laser data using intensity and geometry features
AU - Wang, Zhi
AU - Brenner, Claus
N1 - Funding Information: Acknowledgements. This work was developed with the collaboration of the CNR-IRPI, Perugia. We are grateful to Mauro Rossi, Fausto Guzzetti, Francesca Ardizzone, Paola Reichenbach and Ivan Marchesini. Mauro Rossi prepared a script of the Combination Model for the R free software environment for statistical computing. The script is available for download at the universal resource locator address: http://geomorphology.irpi.cnr.it/tools/landslide-susceptibility-assessment/r-script-for-landslide-susceptibility-assessment-by-mauro-rossi. Thanks are also due to CONACyT for providing support for the project 156242.
PY - 2008
Y1 - 2008
N2 - Terrestrial laser scanning provides a three-dimensional sampled representation of the surfaces of terrestrial objects. The fully automatic registration of terrestrial laser scanning point-clouds is still a question as it involves handling huge datasets, irregular point distribution, multiple views, and relatively low textured surfaces. In this paper, we propose a key point based method using intensity and geometry features for the automatic marker-free registration of terrestrial laser scans. We apply the SIFT method for extracting feature points from the reflectance image and geometric constraint for excluding false matches. To evaluate the performance of proposed method, we employ a test scene in downtown Hannover, Germany. Reference orientations were acquired by the standard orientation procedure using retro-reflective targets and manually assisted target selection. In the experiments, we present the results of the proposed method regarding performance, accuracy and running time for the test scene.
AB - Terrestrial laser scanning provides a three-dimensional sampled representation of the surfaces of terrestrial objects. The fully automatic registration of terrestrial laser scanning point-clouds is still a question as it involves handling huge datasets, irregular point distribution, multiple views, and relatively low textured surfaces. In this paper, we propose a key point based method using intensity and geometry features for the automatic marker-free registration of terrestrial laser scans. We apply the SIFT method for extracting feature points from the reflectance image and geometric constraint for excluding false matches. To evaluate the performance of proposed method, we employ a test scene in downtown Hannover, Germany. Reference orientations were acquired by the standard orientation procedure using retro-reflective targets and manually assisted target selection. In the experiments, we present the results of the proposed method regarding performance, accuracy and running time for the test scene.
KW - Algorithms
KW - Geometry
KW - Laser scanning
KW - Point cloud
KW - Registration
KW - TLS
UR - http://www.scopus.com/inward/record.url?scp=84970903020&partnerID=8YFLogxK
M3 - Conference article
AN - SCOPUS:84970903020
VL - 37
SP - 583
EP - 589
JO - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
JF - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
SN - 1682-1750
T2 - 2008 21st ISPRS International Congress for Photogrammetry and Remote Sensing
Y2 - 3 July 2008 through 11 July 2008
ER -