LiDAR and Camera Calibration Using Near-Far Dual Targets

Abstract

Due to different modality and sampling density between LiDAR and camera, the correspondences between these two sensors are difficult to find. In this paper, we propose a novel method for Camera-LiDAR extrinsic parameters calibration based on the near-far dual targets. In our approach, a chessboard target is placed closer to the combined Camera-LiDAR device and a trihedron object of the structured scene is placed farther. Using the chessboard, camera motion can be estimated through the RGB images captured by the camera. The point cloud captured by LiDAR from the trihedron is then used for LiDAR motion estimation. By coordinating their motion constraints, our approach can reliably estimate the extrinsic parameters between two sensors by a classic hand-eye calibration process without facing the challenges of finding feature correspondences. Finally, the proposed method is evaluated on both simulated data and real data.