Automatic Registration of Terrestrial and Airborne Point Clouds Using Building Outline Features

Abstract

Terrestrial laser scanner (TLS) and airborne laser scanner (ALS) can effectively capture point clouds from side or top view, respectively. Registering point clouds captured by ALS and TLS provides an integrated data source for three-dimensional (3-D) reconstruction. However, registration is difficult between TLS and ALS data because of the differences in scanning perspectives, scanning area, and spatial resolutions. A new method that can achieve automatic horizontal registration with ALS and TLS data based on building contour features is proposed in this study. The key steps include horizontal and vertical registrations based on 2-D building outlines and ground planes in ALS and TLS data, respectively. First, the 2-D building outlines are extracted from both ALS and TLS data. Second, the horizontal registration is accomplished by using the four-point congruent sets method for initial registration and the global optimization method for refined registration. Finally, the ground surface in the same region of ALS and TLS data are fitted for vertical registration, and the average elevation difference between the corresponding ground planes is calculated as the translation parameter value in the vertical direction. The results indicate that the proposed method can successfully match ALS and TLS data with an accuracy of 0.2-m both in the horizontal and vertical directions.