MFCalib: マルチ特徴エッジに基づくターゲットレス環境でのLiDAR-カメラ単一ショット自動外部キャリブレーション
MFCalib: Single-shot and Automatic Extrinsic Calibration for LiDAR and Camera in Targetless Environments Based on Multi-Feature Edge
ターゲット不要の環境で、LiDARとRGBカメラの外部キャリブレーションを1回のデータ取得で自動的に行う手法を提案。深度連続・不連続エッジと輝度不連続エッジを組み合わせ、LiDARビームモデルでエッジ膨張を抑制し、高精度なキャリブレーションを実現した。
著者: Tianyong Ye, Wei Xu, Chunran Zheng, Yukang Cui
分類: cs.RO
原文アブストラクト
This paper presents MFCalib, an innovative extrinsic 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 extraction strategy ensures our ability to achieve accurate calibration with just one round of data collection, even in complex and varied 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 community development, we make our code available open-source on GitHub.
