Volume XLII-2
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 1207-1212, 2018
https://doi.org/10.5194/isprs-archives-XLII-2-1207-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 1207-1212, 2018
https://doi.org/10.5194/isprs-archives-XLII-2-1207-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  30 May 2018

30 May 2018

PLANE-BASED REGISTRATION OF SEVERAL THOUSAND LASER SCANS ON STANDARD HARDWARE

D. Wujanz1, S. Schaller2, F. Gielsdorf3, and L. Gründig3 D. Wujanz et al.
  • 1Technische Universität Berlin, Berlin, Germany
  • 2Zimmermann & Meixner 3D WELT GmbH, Fohlenweide 41, 88279 Amtzell, Germany
  • 3technet GmbH, Am Lehnshof 8, 13467 Berlin, Germany

Keywords: Terrestrial laser scanning, registration, plane-to-plane correspondences, stochastic modelling, large networks

Abstract. The automatic registration of terrestrial laser scans appears to be a solved problem in science as well as in practice. However, this assumption is questionable especially in the context of large projects where an object of interest is described by several thousand scans. A critical issue inherently linked to this task is memory management especially if cloud-based registration approaches such as the ICP are being deployed. In order to process even thousands of scans on standard hardware a plane-based registration approach is applied. As a first step planar features are detected within the unregistered scans. This step drastically reduces the amount of data that has to be handled by the hardware. After determination of corresponding planar features a pairwise registration procedure is initiated based on a graph that represents topological relations among all scans. For every feature individual stochastic characteristics are computed that are consequently carried through the algorithm. Finally, a block adjustment is carried out that minimises the residuals between redundantly captured areas. The algorithm is demonstrated on a practical survey campaign featuring a historic town hall. In total, 4853 scans were registered on a standard PC with four processors (3.07 GHz) and 12 GB of RAM.