Extrinsic calibration of Velodyne-VLP16 LiDAR and camera using only three 3D-2D correspondences

Abstract

The composition of multiple-layer Light Detection And Ranging (LiDAR) and camera is commonly used in autonomous perception systems. Complementary information of these sensors is instrumental in the reliable surrounding perception. However, it is a difficult work for obtaining the extrinsic parameters between LiDAR and camera, which must be known for some perception algorithms. In this study, we present a method, using only three 3D-2D correspondences to compute the extrinsic parameters between Velodyne-VLP16 LiDAR and monocular camera. The procedure is that 3D and 2D features are extracted respectively from the point cloud and image of a custom calibration target and then the extrinsic parameters are obtained based on these features by the perspective-3-point (P3P) algorithm. Outliers with minimum energy at geometrical discontinuities of target are used as control points for extracting key features in LiDAR point cloud. Moreover, a novel method is presented to distinguish the correct solution from multiple P3P solutions. The method depends on conic shape discrepancies in spaces of the different solutions.