Object Modeling from 3D Point Cloud Data for Self-Driving Vehicles

For autonomous vehicles to be deployed and used practically, many problems are still needed to be solved. One of them we are interested in is to make use of a cheap LIDAR for robust object modelling with 3D point cloud data. Self-driving vehicles require accurate information about the surrounding environments to decide the next course of actions. 3D point cloud data obtained from LIDAR give more accurate distance than the counterpart stereo images. As LIDAR generates lowresolution data, the object detection and modeling is prone to produce errors. In this work, we propose the use of multiple frames of LIDAR data in an urban environment to construct a comprehensive model of the object. We assume the use of LIDAR on a moving platform and the results are almost equal to the 3D CAD model representation of the object.