Extraction and Simplification of Building Façade Pieces from Mobile Laser Scanner Point Clouds for 3D Street View Services

Extraction and analysis of building façades are key processes in the three-dimensional (3D) building reconstruction and realistic geometrical modeling of the urban environment, which includes many applications, such as smart city management, autonomous navigation through the urban environment, fly-through rendering, 3D street view, virtual tourism, urban mission planning, etc. This paper proposes a building facade pieces extraction and simplification algorithm based on morphological filtering with point clouds obtained by a mobile laser scanner (MLS). First, this study presents a point cloud projection algorithm with high-accuracy orientation parameters from the position and orientation system (POS) of MLS that can convert large volumes of point cloud data to a raster image. Second, this study proposes a feature extraction approach based on morphological filtering with point cloud projection that can obtain building facade features in an image space. Third, this study designs an inverse transformation of point cloud projection to convert building facade features from an image space to a 3D space. A building facade feature with restricted facade plane detection algorithm is implemented to reconstruct façade pieces for street view service. The results of building facade extraction experiments with large volumes of point cloud from MLS show that the proposed approach is suitable for various types of building facade extraction. The geometric accuracy of building façades is 0.66 m in x direction, 0.64 in y direction and 0.55 m in the vertical direction, which is the same level as the space resolution (0.5 m) of the point cloud.