FAST-Calib: LiDAR-Camera Extrinsic Calibration in One Second
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Abstract (arXiv)
This paper proposes FAST-Calib, a fast and user-friendly LiDAR-camera extrinsic calibration tool based on a custom-made 3D target. FAST-Calib supports both mechanical and solid-state LiDARs by leveraging an efficient and reliable edge extraction algorithm that is agnostic to LiDAR scan patterns. It also compensates for edge dilation artifacts caused by LiDAR spot spread through ellipse fitting, and supports joint optimization across multiple scenes. We validate FAST-Calib on three LiDAR models (Ouster, Avia, and Mid360), each paired with a wide-angle camera. Experimental results demonstrate superior accuracy and robustness compared to existing methods. With point-to-point registration errors consistently below 6.5mm and total processing time under 0.7s, FAST-Calib provides an efficient, accurate, and target-based automatic calibration pipeline. We have open-sourced our code and dataset on GitHub to benefit the robotics community.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 23 Jul 2025.
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Citing papers per year: 2026: 3.
3 papers.
- 2026UMI-3D: Extending Universal Manipulation Interface from Vision-Limited to 3D Spatial Perceptioncited by 4
- 2026Semantic-ITC: A Frame-wise Indoor Mobile Laser Scanning Dataset and Benchmark for Semantic Segmentationcited by 0
- 2026MIRAGE: Metric Inference and Reliability-Aware Gaussian Estimation from Feed-Forward Visioncited by 0
- 2026MIRAGE: Metric Inference and Reliability-Aware Gaussian Estimation from Feed-Forward Vision8 Oct 2026
- 2026Semantic-ITC: A Frame-wise Indoor Mobile Laser Scanning Dataset and Benchmark for Semantic Segmentation16 Sep 2026
- 2026UMI-3D: Extending Universal Manipulation Interface from Vision-Limited to 3D Spatial Perception15 Apr 2026