A Step-By-Step Approach for Camera and Low-Resolution-3D-LiDAR Calibration

Hasan Abbasi, Ankita Dey, Ian Lam, Ziaaddin Sharifisoraki, Ebrahim Ali, Marzieh Amini, Sreeraman Rajan, James R. Green, Felix Kwamena

Abstract: Camera-LiDAR data fusion is being increasingly used to enhance accuracy in perception systems for various applications including autonomous vehicles and smart monitoring. Object detection and semantic segmentation techniques are applied to the data captured by multi-modal sensors, such as a camera and a LiDAR, to perceive the environment. To obtain high accuracy in the fusion of these sensor modalities, one requires precise sensor calibration. While different camera-LiDAR calibration methods have been published in recent years, practical tutorial-style instructions are not available to researchers. In this paper, we present a step-by-step calibration process to determine the correspondence between a camera and LiDAR. This procedure is implemented in MATLAB which makes it easier for novice researchers to extend it for their applications including the ones with low-resolution LiDAR. The implemented code is made publicly available in the GitHub repository at https://github.com/ Multimedia-Research-Lab-Carleton Uzcamera-lidar-calibratlon.ait.