MFCalib: Single-Shot and Automatic Extrinsic Calibration for LiDAR and Camera in Targetless Environments Based on Multi-Feature Edge

This paper presents MFCalib, an innovative ex- trinsic calibration technique for LiDAR and RGB camera that operates automatically in targetless environments with a single data capture. At the heart of this method is using a rich set of edge information, significantly enhancing calibration accuracy and robustness. Specifically, we extract both depth- continuous and depth-discontinuous edges, along with intensity- discontinuous edges on planes. This comprehensive edge extrac- tion strategy ensures our ability to achieve accurate calibration with just one round of data collection, even in complex and var- ied settings. Addressing the uncertainty of depth-discontinuous edges, we delve into the physical measurement principles of LiDAR and develop a beam model, effectively mitigating the issue of edge inflation caused by the LiDAR beam. Extensive experiment results demonstrate that MFCalib outperforms the state-of-the-art targetless calibration methods across various scenes, achieving and often surpassing the precision of multi- scene calibrations in a single-shot collection. To support com- munity development, we make our code available open-source on GitHub.