On the effectiveness of feature-based lidar point cloud registration

J. J. Jaw*, T. Y. Chuang

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

2 Scopus citations


LIDAR systems have been regarded as novel technologies for efficiently acquiring 3-D geo-spatial information, resulting in broad applications in engineering and management fields. Registration of LIDAR point clouds of consecutive scans or different platforms is a prerequisite for fully exploiting advantages of afore-mentioned applications. In this study, the authors integrate point, line and plane features, commonly seen geometric primitives and readily detected or derived from point clouds, for establishing a multi-feature 3-D similarity transformation model, both functional and stochastic, and illustrate the feasibility of the proposed methodologies on the effectiveness of employed features through theoretical identifications and experimental demonstrations.

Original languageEnglish
Pages (from-to)60-65
Number of pages6
JournalInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
StatePublished - 2010
EventISPRS Technical Commission III Symposium on Photogrammetric Computer Vision and Image Analysis, PCV 2010 - Saint-Mande, France
Duration: 1 Sep 20103 Sep 2010


  • 3-D similarity transformation model
  • Feature-based
  • Registration

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