TOWARDS 4D VIRTUAL CITY RECONSTRUCTION FROM LIDAR POINT CLOUD SEQUENCES
In this paper we propose a joint approach on virtual city reconstruction and dynamic scene analysis based on point cloud sequences of a single car-mounted Rotating Multi-Beam (RMB) Lidar sensor. The aim of the addressed work is to create 4D spatio-temporal models of large dynamic urban scenes containing various moving and static objects. Standalone RMB Lidar devices have been frequently applied in robot navigation tasks and proved to be efficient in moving object detection and recognition. However, they have not been widely exploited yet for geometric approximation of ground surfaces and building facades due to the sparseness and inhomogeneous density of the individual point cloud scans. In our approach we propose an automatic registration method of the consecutive scans without any additional sensor information such as IMU, and introduce a process for simultaneously extracting reconstructed surfaces, motion information and objects from the registered dense point cloud completed with point time stamp information.