CC BY 4.0Gehrung, JoachimJoachimGehrungHebel, MarcusMarcusHebelArens, MichaelMichaelArensStilla, UweUweStilla2022-03-138.6.20172017https://publica.fraunhofer.de/handle/publica/39672110.5194/isprs-annals-IV-1-W1-107-2017Data 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.envolumetric representationbackground subtractionDetection and Tracking of Mobile Objectschange detection004670conference paper