Estimating extrinsic parameters between a stereo rig and a multi-layer lidar using plane matching and circle feature extraction

In this work, we investigate the problem of estimating a rigid transform mapping between a calibrated stereo camera rig and a multi-layer lidar. Such a transform may be used to merge data between these 2 systems, addressing the colourless sparse nature of the lidar data and potentially improving depth estimation from the stereo pairs. The proposed approach features a novel planar calibration object with three circular features allowing for the robust acquisition of corresponding features between sensors. A closed-form registration of correspondences is proposed, leading to the derivation of the required transform. The main appeal of the proposed approach is its conceptually simple formulation and the fact that only a single image from each device is required for calibration. Our experiments were performed on real data captured in outdoor and indoor environments and demonstrate good performance with a Velodyne VLP-16 lidar and GOPRO HERO 3+ Stereo rig.