LiDAR-camera Calibration using Intensity Variance Cost

We propose an extrinsic calibration method for LiDAR-camera fusion systems using variations in intensities projected from camera images to the LiDAR point cloud. As the input, the proposed method uses a sequence of LiDAR data and camera images captured while moving the system. Once the camera motion is calculated, camera images are projected onto the point cloud. The variations in the projected intensities at each point are large in the presence of errors in the estimated motion or calibration parameters. Consequently, the extrinsic parameters are optimized for cost minimization based on the intensity variance. In addition, a suitable geometry is proposed for the calibration and verified using simulations. Our experimental results showed that the proposed method accurately performed calibrations using a camera and a sparse multi-beam LiDAR or one-dimensional LiDAR.