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Registration of colored 3D point clouds with a Kernel-based extension to the normal distributions transform
Department of Graphical Interactive Systems WSI/GRIS, University of Tübingen, Germany. (WSI/GRIS)
Örebro University, Department of Technology. (AASS)ORCID iD: 0000-0001-8658-2985
Department of Graphical Interactive Systems WSI/GRIS, University of Tübingen, Germany. (WSI/GRIS)
Örebro University, Department of Technology. (AASS)ORCID iD: 0000-0003-0217-9326
2008 (English)In: 2008 IEEE international conference on robotics and automation, New York, NY, USA: IEEE, 2008, p. 4025-4030, article id 4543829Conference paper, Published paper (Refereed)
Abstract [en]

We present a new algorithm for scan registration of colored 3D point data which is an extension to the Normal Distributions Transform (NDT). The probabilistic approach of NDT is extended to a color-aware registration algorithm by modeling the point distributions as Gaussian mixture-models in color space. We discuss different point cloud registration techniques, as well as alternative variants of the proposed algorithm. Results showing improved robustness of the proposed method using real-world data acquired with a mobile robot and a time-of-flight camera are presented.

Place, publisher, year, edition, pages
New York, NY, USA: IEEE, 2008. p. 4025-4030, article id 4543829
Series
IEEE International Conference on Robotics and Automation ICRA, ISSN 1050-4729
National Category
Engineering and Technology Computer and Information Sciences
Research subject
Computer and Systems Science
Identifiers
URN: urn:nbn:se:oru:diva-4720DOI: 10.1109/ROBOT.2008.4543829ISI: 000258095002207Scopus ID: 2-s2.0-51649107894ISBN: 978-1-4244-1646-2 (print)OAI: oai:DiVA.org:oru-4720DiVA, id: diva2:139019
Conference
IEEE international conference on robotics and automation, ICRA 2008, Pasadena, CA, USA, 19-23 May 2008
Available from: 2008-11-12 Created: 2008-11-12 Last updated: 2018-06-13Bibliographically approved

Open Access in DiVA

Registration of Colored 3D Point Clouds with a Kernel-based Extension to the Normal Distributions Transform(1102 kB)3 downloads
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File name FULLTEXT01.pdfFile size 1102 kBChecksum SHA-512
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Type fulltextMimetype application/pdf

Other links

Publisher's full textScopushttp://aass.oru.se/~mmn/bh_mm_ws_al_icra2008.pdf

Authority records BETA

Magnusson, MartinLilienthal, Achim J.

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