Registration of Image and 3D LIDAR Data from Extrinsic Calibration

Camera and laser rangefinder (LRF) are widely used in various mobilized systems, such as intelligent vehicle, autonomous robot, etc. And extrinsic calibration is essential and basically the first step to integrate image and 3D LIDAR data. This paper presents a flexible method for extrinsic calibration of a pin-hole camera and a 3D Laser Rangefinder (LRF). The method extends the chessboard pattern, which is originally used for camera calibration, for camera and 2D LRF calibration. It requires at least 3 input planes to determine the rotation and translation between these two sensors. The proposed method formulates the extrinsic calibration problem as to register point correspondences in the dual 3D space instead of plane registration in 3D space. And the rotation matrix and the translation vector are estimated separately. The extrinsic calibration results allow the registration of image and 3D LIDAR data by mapping all the LIDAR data onto the imaging plane. The proposed method has been tested with both simulation and real data. The experimental results show that the proposed algorithm is both accurate and practical.