Abstract
ABSTRACT Mobile laser scanning data can be used for effective extraction of road edge information, which is important in the domain of road maintenance and intelligent transportation. This paper proposes a road edge detection method that combines a deep learning and spatial statistics of point cloud data. Semantic segmentation using a deep neural network enables the effective extraction of point cloud fragments recognized as road. The process continues with the spatial statistical analysis of voxel features of data organized into a 3D voxel grid. Filtered voxels are clustered into spatially proximate clusters of similar shape, i.e. straight or curved edges.
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