2022 年 10 巻 1 号 p. 2-10
Planes are simple shapes often found in urban environments. Their detection is crucial for several applications of 3D point clouds. Efforts have focused on detecting planes in low-cost and lowrange scenarios. However, in Terrestrial Laser Scanning (TLS), the range is extended to a few hundred meters. This long-range adds huge variations in points’ density that complicates defining proper thresholds for conventional methods. Therefore, we propose to employ the sliding voxel plane detector over multiple voxel sizes to estimate hypothetical planes in a coarse-to-fine way, followed by a merging Non-Maximum Suppression to detect planes robustly. According to experimental results, the proposed method shows superior precision, efficiency, and scalability in TLS point clouds.
