Point based registration of terrestrial laser data using intensity and geometry features

Publikation: Beitrag in FachzeitschriftKonferenzaufsatz in FachzeitschriftForschungPeer-Review

Autorschaft

  • Zhi Wang
  • Claus Brenner

Externe Organisationen

  • Wuhan University
Forschungs-netzwerk anzeigen

Details

OriginalspracheEnglisch
Seiten (von - bis)583-589
Seitenumfang7
FachzeitschriftInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
Jahrgang37
PublikationsstatusVeröffentlicht - 2008
Veranstaltung2008 21st ISPRS International Congress for Photogrammetry and Remote Sensing - Beijing, China
Dauer: 3 Juli 200811 Juli 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.

ASJC Scopus Sachgebiete

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Point based registration of terrestrial laser data using intensity and geometry features. / Wang, Zhi; Brenner, Claus.
in: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, Jahrgang 37, 2008, S. 583-589.

Publikation: Beitrag in FachzeitschriftKonferenzaufsatz in FachzeitschriftForschungPeer-Review

Wang, Z & Brenner, C 2008, 'Point based registration of terrestrial laser data using intensity and geometry features', International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, Jg. 37, S. 583-589. <https://www.isprs.org/proceedings/XXXVII/congress/5_pdf/101.pdf>
Wang, Z., & Brenner, C. (2008). Point based registration of terrestrial laser data using intensity and geometry features. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 37, 583-589. https://www.isprs.org/proceedings/XXXVII/congress/5_pdf/101.pdf
Wang Z, Brenner C. Point based registration of terrestrial laser data using intensity and geometry features. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives. 2008;37:583-589.
Wang, Zhi ; Brenner, Claus. / Point based registration of terrestrial laser data using intensity and geometry features. in: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives. 2008 ; Jahrgang 37. S. 583-589.
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title = "Point based registration of terrestrial laser data using intensity and geometry features",
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",
author = "Zhi Wang and Claus Brenner",
note = "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.; 2008 21st ISPRS International Congress for Photogrammetry and Remote Sensing ; Conference date: 03-07-2008 Through 11-07-2008",
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Download

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 -