Volume IV-1
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-1, 85-92, 2018
https://doi.org/10.5194/isprs-annals-IV-1-85-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-1, 85-92, 2018
https://doi.org/10.5194/isprs-annals-IV-1-85-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  26 Sep 2018

26 Sep 2018

AN EVALUATION PIPELINE FOR INDOOR LASER SCANNING POINT CLOUDS

S. Karam, M. Peter, S. Hosseinyalamdary, and G. Vosselman S. Karam et al.
  • Dept. of Earth Observation Science, Faculty ITC, University of Twente, 7514 AE Enschede, The Netherlands

Keywords: Evaluation, Analysis, Point Clouds, SLAM, IMMS, Comparison, Ground Truth

Abstract. The necessity for the modelling of building interiors has encouraged researchers in recent years to focus on improving the capturing and modelling techniques for such environments. State-of-the-art indoor mobile mapping systems use a combination of laser scanners and/or cameras mounted on movable platforms and allow for capturing 3D data of buildings’ interiors. As GNSS positioning does not work inside buildings, the extensively investigated Simultaneous Localisation and Mapping (SLAM) algorithms seem to offer a suitable solution for the problem. Because of the dead-reckoning nature of SLAM approaches, their results usually suffer from registration errors. Therefore, indoor data acquisition has remained a challenge and the accuracy of the captured data has to be analysed and investigated. In this paper, we propose to use architectural constraints to partly evaluate the quality of the acquired point cloud in the absence of any ground truth model. The internal consistency of walls is utilized to check the accuracy and correctness of indoor models. In addition, we use a floor plan (if available) as an external information source to check the quality of the generated indoor model. The proposed evaluation method provides an overall impression of the reconstruction accuracy. Our results show that perpendicularity, parallelism, and thickness of walls are important cues in buildings and can be used for an internal consistency check.