INVENTORY OF 3D STREET LIGHTING POLES USING MOBILE LASER SCANNING POINT CLOUDS

This paper presents a novel approach for extracting street lighting poles directly from MLS point clouds. The approach includes four stages: 1) elevation filtering to remove ground points, 2) Euclidean distance clustering to cluster points, 3) voxel-based normalized cut (Ncut) segmentation to separate overlapping objects, and 4) statistical analysis of geometric properties to extract 3D street lighting poles. A Dataset acquired by a RIEGL VMX-450 MLS system are tested with the proposed approach. The results demonstrate the efficiency and reliability of the proposed approach to extract 3D street lighting poles.