Detection and reconstruction of static vehicle-related ground occlusions in point clouds from mobile laser scanning
نویسندگان
چکیده
Vehicle-related ground occlusion is a common problem in MLS data. This study aims to design detection and reconstruction method of static vehicle-related for Ground extraction vehicle segmentation are performed on the input point cloud data advance. Then an α-shape boundary based prior geometry designed split non-ground empty area occlusions. The detected matched with its corresponding using relative position between them. relation height difference used detect curb direction as local road direction. Finally, occlusions reconstructed two different methods: (1) cell-based linear interpolation (2) point-based mathematical morphology. methodology tested by original scanned multi-temporal evaluation captured from residential Delft, Netherlands vehicle-mounted LiDAR sensors. result shows that all cause vehicles successfully (road) correctly extracted most occluded areas. Both results can visually integrate recover structure. errors 0.045 m z-axis 0.051 total morphology 0.048 0.052 total.
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ژورنال
عنوان ژورنال: Automation in Construction
سال: 2022
ISSN: ['1872-7891', '0926-5805']
DOI: https://doi.org/10.1016/j.autcon.2022.104461