Detailed Analysis on Generating the Range Image for LiDAR Point Cloud Processing

Abstract

Range images are commonly used representations for 3D LiDAR point cloud in the field of autonomous driving. The approach of generating a range image is generally regarded as a standard approach. However, there do exist two different types of approaches to generating the range image: In one approach, the row of the range image is defined as the laser ID, and in the other approach, the row is defined as the elevation angle. We named the first approach Projection By Laser ID (PBID), and the second approach Projection By Elevation Angle (PBEA). Few previous works have paid attention to the difference of these two approaches. In this work, we quantitatively analyze these two different approaches. Experimental results show that the PBEA approach can obtain much smaller quantization errors than PBID, and should be the preferred choice in reconstruction-related tasks. If PBID is chosen for use in recognition-related tasks, then we have to tolerate its larger quantization error.