汎用・単発・ターゲット不要・自動LiDARカメラ外部キャリブレーションツールボックス
General, Single-shot, Target-less, and Automatic LiDAR-Camera Extrinsic Calibration Toolbox
LiDARとカメラの外部キャリブレーションを、ターゲットなしの1回のデータ取得で自動的に行うオープンソースツールボックスを提案。SuperGlueによる初期対応推定と相互情報量に基づく直接位置合わせで高精度・高ロバストにキャリブレーションする。
著者: Kenji Koide, Shuji Oishi, Masashi Yokozuka, Atsuhiko Banno
分類: cs.RO
原文アブストラクト
This paper presents an open source LiDAR-camera calibration toolbox that is general to LiDAR and camera projection models, requires only one pairing of LiDAR and camera data without a calibration target, and is fully automatic. For automatic initial guess estimation, we employ the SuperGlue image matching pipeline to find 2D-3D correspondences between LiDAR and camera data and estimate the LiDAR-camera transformation via RANSAC. Given the initial guess, we refine the transformation estimate with direct LiDAR-camera registration based on the normalized information distance, a mutual information-based cross-modal distance metric. For a handy calibration process, we also present several assistance capabilities (e.g., dynamic LiDAR data integration and user interface for making 2D-3D correspondence manually). The experimental results show that the proposed toolbox enables calibration of any combination of spinning and non-repetitive scan LiDARs and pinhole and omnidirectional cameras, and shows better calibration accuracy and robustness than those of the state-of-the-art edge-alignment-based calibration method.
