Segment-based Classification of Mobile Lidar Point Clouds with Limited Samples

Abstract

Mobile lidar data have been widely used in building 3D models, road mapping and inventorying, and nowadays in driverless car technology. Compared with traditional photogrammetry and remote sensing data acquisition methods, mobile lidar technology can collect precise 3D point cloud data more efficiently at driving speeds in urban environments, even in extreme weather conditions. Efficient processing of mobile lidar data, including object detection and recognition, is an active research field. Manual object detection and labelling is tedious, and it is limited by the variety of objects and the complexity of the environments in which the data is acquired. Therefore, the development of automated..