Occluded Boundary Detection for Small-Footprint Groundborne LIDAR Point Cloud Guided by Last Echo

Abstract

Occluded boundary detection in a 3-D point cloud is an indispensable preprocessing step for many applications, such as point cloud completion. Meanwhile, existing methods do not have the ability of distinguishing occluded and complete surface borders, such as the border of a sign board. To solve this problem, this letter presents an occluded boundary detection method for small-footprint LIDAR point clouds. The main novelty of this letter is using the last-echo information for occluded boundary detection. Seed boundary (SB) points are subsequently detected using this last-echo information. Finally, the SB points are grown into neighboring points using an occluded boundary growth algorithm. To the best of our knowledge, this method is the first method that uses the last-echo information to detect occluded boundaries. Experimental results with comparisons indicate that the proposed method can accurately and efficiently detect an occluded boundary without contamination from a complete surface border. These advantages allow the proposed method to benefit further applications such as point cloud completion, as demonstrated in the application section.