A Method for the Calibration of a LiDAR and Fisheye Camera System

Abstract

LiDAR and camera systems are frequently used together to gain a more complete understanding of the environment in different fields, such as mobile robotics, autonomous driving, or intelligent surveillance. Accurately calibrating the extrinsic parameters is crucial for the accurate fusion of the data captured by both systems, which is equivalent to finding the transformation between the reference systems of both sensors. Traditional calibration methods for LiDAR and camera systems are developed for pinhole cameras and are not directly applicable to fisheye cameras. This work proposes a target-based calibration method for LiDAR and fisheye camera systems that avoids the need to transform images to a pinhole camera model, reducing the computation time. Instead, the method uses the spherical projection of the image, obtained with the intrinsic calibration parameters and the corresponding point cloud for LiDAR–fisheye calibration. Thus, unlike a pinhole-camerabased system, a wider field of view is provided, adding more information, which will lead to a better understanding of the environment itself, as well as enabling using fewer image sensors to cover a wider area.