ISPRS-Annals ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences ISPRS-Annals ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci. 2194-9050 Copernicus Publications Göttingen, Germany 10.5194/isprs-annals-IV-1-W1-107-2017 AN APPROACH TO EXTRACT MOVING OBJECTS FROM MLS DATA USING A VOLUMETRIC BACKGROUND REPRESENTATION Gehrung J. 1 2 Hebel M. 1 Arens M. 1 Stilla U. https://orcid.org/0000-0002-1184-0924 2 Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB, 76275 Ettlingen, Germany Photogrammetry and Remote Sensing, Technische Universitaet Muenchen, 80333 Muenchen, Germany 30 05 2017 IV-1/W1 107 114 Copyright: © 2017 J. Gehrung et al. 2017 This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/3.0/ This article is available from https://isprs-annals.copernicus.org/articles/IV-1-W1/107/2017/isprs-annals-IV-1-W1-107-2017.html The full text article is available as a PDF file from https://isprs-annals.copernicus.org/articles/IV-1-W1/107/2017/isprs-annals-IV-1-W1-107-2017.pdf

Data recorded by mobile LiDAR systems (MLS) can be used for the generation and refinement of city models or for the automatic detection of long-term changes in the public road space. Since for this task only static structures are of interest, all mobile objects need to be removed. This work presents a straightforward but powerful approach to remove the subclass of moving objects. A probabilistic volumetric representation is utilized to separate MLS measurements recorded by a Velodyne HDL-64E into mobile objects and static background. The method was subjected to a quantitative and a qualitative examination using multiple datasets recorded by a mobile mapping platform. The results show that depending on the chosen octree resolution 87-95% of the measurements are labeled correctly.