Volume IV-1/W1
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-1/W1, 107-114, 2017
https://doi.org/10.5194/isprs-annals-IV-1-W1-107-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-1/W1, 107-114, 2017
https://doi.org/10.5194/isprs-annals-IV-1-W1-107-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

  30 May 2017

30 May 2017

AN APPROACH TO EXTRACT MOVING OBJECTS FROM MLS DATA USING A VOLUMETRIC BACKGROUND REPRESENTATION

J. Gehrung1,2, M. Hebel1, M. Arens1, and U. Stilla2 J. Gehrung et al.
  • 1Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB, 76275 Ettlingen, Germany
  • 2Photogrammetry and Remote Sensing, Technische Universitaet Muenchen, 80333 Muenchen, Germany

Keywords: Volumetric Representation, Background Subtraction, Detection and Tracking of Mobile Objects, Change Detection

Abstract. 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.