Details
| Original language | English |
|---|---|
| Journal | International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives |
| Volume | 36 |
| Issue number | 5/W17 |
| Publication status | Published - 2005 |
| Event | 2005 Virtual Reconstruction and Visualization of Complex Architectures, 3D-ARCH 2005 - Mestre-Venice, Italy Duration: 22 Aug 2005 → 24 Aug 2005 |
Abstract
The registration of scan data often uses special markers which are placed in the scene. This leads to a reliable registration but the method is not very efficient. Therefore, we search for a registration method which works without markers. There are methods like the iterative closest point (ICP) algorithm which calculate the registration on the basis of the data itself. However, these algorithms have a small convergence radius and therefore a manual pre-alignment is necessary. In this paper, we explore a registration method called the normal distribution transform (NDT) which does not require markers, has a larger convergence radius than ICP and a medium alignment accuracy. The NDT was initially proposed in robotics for single-plane horizontal scans. We investigate three modifications to the original algorithm: a coarse-tofine strategy, multiple slices, and iterative solution using the method of Levenberg-Marquardt. We apply the modified algorithm to real terrestrial laser scanner data and discuss the results.
Keywords
- Laser scanning, LIDAR, Matching, Registration, Terrestrial
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. 36, No. 5/W17, 2005.
Research output: Contribution to journal › Conference article › Research › peer review
}
TY - JOUR
T1 - Marker-free registration of terrestrial laser scans using the normal distribution transform
AU - Ripperda, Nora
AU - Brenner, Claus
N1 - Funding Information: This work was done within in the scope of the junior research group “Automatic methods for the fusion, reduction and consistent combination of complex, heterogeneous geoinformation”, funded by the VolkswagenStiftung, Germany.
PY - 2005
Y1 - 2005
N2 - The registration of scan data often uses special markers which are placed in the scene. This leads to a reliable registration but the method is not very efficient. Therefore, we search for a registration method which works without markers. There are methods like the iterative closest point (ICP) algorithm which calculate the registration on the basis of the data itself. However, these algorithms have a small convergence radius and therefore a manual pre-alignment is necessary. In this paper, we explore a registration method called the normal distribution transform (NDT) which does not require markers, has a larger convergence radius than ICP and a medium alignment accuracy. The NDT was initially proposed in robotics for single-plane horizontal scans. We investigate three modifications to the original algorithm: a coarse-tofine strategy, multiple slices, and iterative solution using the method of Levenberg-Marquardt. We apply the modified algorithm to real terrestrial laser scanner data and discuss the results.
AB - The registration of scan data often uses special markers which are placed in the scene. This leads to a reliable registration but the method is not very efficient. Therefore, we search for a registration method which works without markers. There are methods like the iterative closest point (ICP) algorithm which calculate the registration on the basis of the data itself. However, these algorithms have a small convergence radius and therefore a manual pre-alignment is necessary. In this paper, we explore a registration method called the normal distribution transform (NDT) which does not require markers, has a larger convergence radius than ICP and a medium alignment accuracy. The NDT was initially proposed in robotics for single-plane horizontal scans. We investigate three modifications to the original algorithm: a coarse-tofine strategy, multiple slices, and iterative solution using the method of Levenberg-Marquardt. We apply the modified algorithm to real terrestrial laser scanner data and discuss the results.
KW - Laser scanning
KW - LIDAR
KW - Matching
KW - Registration
KW - Terrestrial
UR - http://www.scopus.com/inward/record.url?scp=85048909914&partnerID=8YFLogxK
M3 - Conference article
AN - SCOPUS:85048909914
VL - 36
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
IS - 5/W17
T2 - 2005 Virtual Reconstruction and Visualization of Complex Architectures, 3D-ARCH 2005
Y2 - 22 August 2005 through 24 August 2005
ER -