Abstract
Large-scale 3D point clouds (LS3DPCs) captured by terrestrial LiDAR scanners often exhibit reflection artifacts by
glasses, which degrade the performance of related computer vision techniques. In this paper, we propose an ef-
ficient reflection removal algorithm for LS3DPCs. We first
partition the unit sphere into local surface patches which
are then classified into the ordinary patches and the glass
patches according to the number of echo pulses from emitted laser pulses. Then we estimate the glass region of dominant reflection artifacts by measuring the reliability. We
also detect and remove the virtual points using the conditions of the reflection symmetry and the geometric similarity. We test the performance of the proposed algorithm on
LS3DPCs capturing real-world outdoor scenes, and show
that the proposed algorithm estimates valid glass regions
faithfully and removes the virtual points caused by reflection artifacts successfully