AN APPROACH TO EXTRACT MOVING OBJECTS FROM MLS DATA USING A VOLUMETRIC BACKGROUND REPRESENTATION
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 presen...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2017-05-01
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| Series: | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/IV-1-W1/107/2017/isprs-annals-IV-1-W1-107-2017.pdf |
| Summary: | 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. |
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| ISSN: | 2194-9042 2194-9050 |