Efficient segmentation of 3D LIDAR point clouds handling partial occlusion

This paper presents a novel approach to segmentation of a dense 3D point cloud, generated by a flash lidar type camera. Incorporating symmetries of the sensor, the algorithm is using a 2D grid approach to cluster data points and extrude object segments in complex scenes. The data representation allows for the handling of partially occluded, but connected objects at different ranges. The algorithm was tested on a variety of different sensor data sets and the obtained results are presented and discussed.