Details
| Originalsprache | Englisch |
|---|---|
| Seiten (von - bis) | 790-799 |
| Seitenumfang | 10 |
| Fachzeitschrift | Sensor Letters |
| Jahrgang | 11 |
| Ausgabenummer | 5 |
| Publikationsstatus | Veröffentlicht - 1 Mai 2013 |
Abstract
Driven by progress in sensor technology, algorithms and data processing capabilities, terrestrial laser sensor has found a wide range of new application fields over the past two decades. Terrestrial laser sensor directly delivers 3D points through an array of coordinates (point cloud) and 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 reflectance 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 intensity image and geometric constraint for excluding false matches. To evaluate the performance of proposed method, we employ a test scene "Holzmarkt" in downtown Hannover, Germany. Reference orientations are 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.
ASJC Scopus Sachgebiete
- Physik und Astronomie (insg.)
- Atom- und Molekularphysik sowie Optik
- Ingenieurwesen (insg.)
- Elektrotechnik und Elektronik
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in: Sensor Letters, Jahrgang 11, Nr. 5, 01.05.2013, S. 790-799.
Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review
}
TY - JOUR
T1 - Automatic registration of terrestrial laser sensor scans using reflectance intensity and geometry features
AU - Wang, Zhi
AU - Li, Huiying
AU - Brenner, Claus
PY - 2013/5/1
Y1 - 2013/5/1
N2 - Driven by progress in sensor technology, algorithms and data processing capabilities, terrestrial laser sensor has found a wide range of new application fields over the past two decades. Terrestrial laser sensor directly delivers 3D points through an array of coordinates (point cloud) and 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 reflectance 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 intensity image and geometric constraint for excluding false matches. To evaluate the performance of proposed method, we employ a test scene "Holzmarkt" in downtown Hannover, Germany. Reference orientations are 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 - Driven by progress in sensor technology, algorithms and data processing capabilities, terrestrial laser sensor has found a wide range of new application fields over the past two decades. Terrestrial laser sensor directly delivers 3D points through an array of coordinates (point cloud) and 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 reflectance 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 intensity image and geometric constraint for excluding false matches. To evaluate the performance of proposed method, we employ a test scene "Holzmarkt" in downtown Hannover, Germany. Reference orientations are 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 - Point Cloud
KW - Reflectance Intensity.
KW - Registration
KW - Sensor
KW - Terrestrial Laser Scanning
UR - http://www.scopus.com/inward/record.url?scp=84887967132&partnerID=8YFLogxK
U2 - 10.1166/sl.2013.2664
DO - 10.1166/sl.2013.2664
M3 - Article
AN - SCOPUS:84887967132
VL - 11
SP - 790
EP - 799
JO - Sensor Letters
JF - Sensor Letters
SN - 1546-198X
IS - 5
ER -