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An approach to extract moving objects from MLS data using a volumetric background representation

: Gehrung, Joachim; Hebel, Marcus; Arens, Michael; Stilla, Uwe

Fulltext urn:nbn:de:0011-n-4460256 (6.0 MByte PDF)
MD5 Fingerprint: 040b1ddbd531cdeb07ec0502fdcc0c8f
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Created on: 8.6.2017

Heipke, C. ; International Society for Photogrammetry and Remote Sensing -ISPRS-:
ISPRS Hannover Workshop 2017 : HRIGI 17 - CMRT 17 - ISA 17 - EuroCOW 17, 6-9 June 2017, Hannover, Germany
Istanbul: ISPRS, 2017 (ISPRS Annals IV-1/W1)
Hannover Workshop "High-Resolution Earth Imaging for Geospatial Information" (HRIGI) <2017, Hannover>
European Calibration and Orientation Workshop (EuroCOW) <2017, Hannover>
Conference Paper, Electronic Publication
Fraunhofer IOSB ()
volumetric representation; background subtraction; Detection and Tracking of Mobile Objects; change detection

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.