Volume IV-2/W5
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2/W5, 271-278, 2019
https://doi.org/10.5194/isprs-annals-IV-2-W5-271-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2/W5, 271-278, 2019
https://doi.org/10.5194/isprs-annals-IV-2-W5-271-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

  29 May 2019

29 May 2019

AUTOMATIC EXTRACTION OF A NAVIGATION GRAPH INTENDED FOR INDOORGML FROM AN INDOOR POINT CLOUD

P. Flikweert1,2, R. Peters3, L. Díaz-Vilariño4,5, R. Voûte2,5, and B. Staats2 P. Flikweert et al.
  • 1Master of Science Geomatics, Faculty of Architecture and the Built Environment, TU Delft, The Netherlands
  • 2CGI Nederland BV, The Netherlands
  • 3Department of Urbanism, Faculty of Architecture and the Built Environment, TU Delft, The Netherlands
  • 4Applied Geotechnologies Group, Dept. of Natural Resources and Environmental Engineering, University of Vigo, Spain
  • 5Department of OTB, Faculty of Architecture and the Built Environment, TU Delft, The Netherlands

Keywords: indoor navigation, IndoorGML, navigation graph, point cloud, voxels, indoor, laser scanning, 3D Medial Axis Transform, automatic door detection

Abstract. Indoor environments tend to be more complex and more populated when buildings are accessible to the public. The need for knowing where people are, how they can get somewhere or how to reach them in these buildings is thus equally increasing. In this research point clouds are used, obtained by dynamic laser scanning of a building, since we cannot rely on architectural drawings for maps and paths, which can be outdated. The presented method focuses on the creation of an indoor navigation graph, based on IndoorGML structure, in a fast and automated way, while retaining the type of walkable surface. In this paper the focus has been on door detection, because doors are essential elements in an indoor environment, seeing that they connect spaces and are a logical step in a route. This paper describes a way to detect doors using 3D Medial Axis Transform (MAT) combined with the intelligence stored in the path of a mobile laser scanner, showing good first results. Additionally different spaces (e.g. rooms and corridors) in the building are identified and slopes and stairs in walkable spaces are detected. This results in a navigation graph which can be stored in an IndoorGML structure.