Automatic Segmentation of Building Facades Using Terrestrial Laser Data

There is an increasing interest of the scientific community in the generation of 3D facade models from terrestrial laser scanner (TLS) data. The segmentation of building facades is one of the essential tasks to be carried out in a 3D modelling process. Since in reality, majority of facade components are planar, the detection and segmentation of geometric elements like planes respond to the previous task. The RANSAC paradigm is a robust estimator and probably the most widely used in the field of computer vision to compute model parameters from a dataset containing outliers. Indeed, RANSAC algorithm is usually successful for fitting geometric primitives to experimental data like for example, 3D point clouds resulting from image matching or from airborne laser scanning. The innovative idea of this study is the application of RANSAC algorithm to TLS data, characterized by a meaningful proportion of outliers. Therefore, this paper presents an approach allowing automatic segmentation and extraction of planar parts of facades scanned by TLS. Firstly, potential planes describing planar surfaces are detected and extracted using RANSAC algorithm. Then, a quality assessment based on manually extracted planes is carried out. The obtained results are evaluated and prove that the proposed method delivers qualitatively as well as quantitatively satisfactory planar facade segments.