Extrinsic Calibration of a 3D-LIDAR and a Camera
This addresses calibration for autonomous systems or robotics, but it is incremental as it builds on existing geometric constraint methods.
The paper tackles the problem of extrinsic calibration between a 3D LIDAR and a camera using a marker-less planar target, achieving parameter estimation by exploiting geometric constraints and validating with specific hardware like Velodyne VLP-32 and Ouster OS1 LIDARs.
This work presents an extrinsic parameter estimation algorithm between a 3D LIDAR and a Projective Camera using a marker-less planar target, by exploiting Planar Surface Point to Plane and Planar Edge Point to back-projected Plane geometric constraints. The proposed method uses the data collected by placing the planar board at different poses in the common field of view of the LIDAR and the Camera. The steps include, detection of the target and the edges of the target in LIDAR and Camera frames, matching the detected planes and lines across both the sensing modalities and finally solving a cost function formed by the aforementioned geometric constraints that link the features detected in both the LIDAR and the Camera using non-linear least squares. We have extensively validated our algorithm using two Basler Cameras, Velodyne VLP-32 and Ouster OS1 LIDARs.