Point Based Registration of Terrestrial Laser Data Using Intensity and Geometry Features

Terrestrial laser scanning provides a three-dimensional sampled representation of the surfaces of terrestrial objects. The fully automatic registration of terrestrial laser scanning point-clouds is still a question as it involves handling huge datasets, irregular point distribution, multiple views, and relatively low textured surfaces. In this paper, we propose a key point based method using intensity and geometry features for the automatic marker-free registration of terrestrial laser scans. We apply the SIFT method for extracting feature points from the reflectance image and geometric constraint for excluding false matches. To evaluate the performance of proposed method, we employ a test scene in downtown Hannover, Germany. Reference orientations were acquired by the standard orientation procedure using retro-reflective targets and manually assisted target selection. In the experiments, we present the results of the proposed method regarding performance, accuracy and running time for the test scene. * Corresponding author: Zhi Wang: [email protected]