In the autonomous driving systems, camera and LiDAR are widely used to recognize surrounding environment. For the fusion of the images and 3D point clouds, it is necessary to conduct calibration between the camera and LiDAR. The existing method utilize the checkerboards for calibration, and the corresponding planes are detected in the images and 3D point clouds of the checkerboards. The checkerboard planes in the images can be detected using the corners of grids on the checkerboard. However, the existing approach has disadvantages of manually extracting plans from 3D LiDAR point cloud to conduct calibration. Therefore, we propose method for automatically extracting planes from LiDAR point cloud using Iterative Closet Point. Also by defining new objective function for optimization, we show that the performance of calibration between the camera and LiDAR is improved in the experimental results.
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