Auto-calibration Method Using Stop Signs for Urban Autonomous Driving Applications
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Abstract (arXiv)
Calibration of sensors is fundamental to robust performance for intelligent vehicles. In natural environments, disturbances can easily challenge calibration. One possibility is to use natural objects of known shape to recalibrate sensors. An approach based on recognition of traffic signs, such as stop signs, and use of them for recalibration of cameras is presented. The approach is based on detection, geometry estimation, calibration, and recursive updating. Results from natural environments are presented that clearly show convergence and improved performance.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 14 Oct 2020.
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Citing papers per year: 2022: 1; 2023: 0; 2024: 1; 2025: 2; 2026: 1.
5 papers.
- 2022V2XP-ASG: Generating Adversarial Scenes for Vehicle-to-Everything Perceptioncited by 28
- 2024Online,Target-Free LiDAR-Camera Extrinsic Calibration via Cross-Modal Mask Matchingcited by 12
- 2025Environment-Driven Online LiDAR-Camera Extrinsic Calibrationcited by 3
- 2025Single-Frame Point-Pixel Registration via Supervised Cross-Modal Feature Matchingcited by 0
- 2026DST-Calib: A Dual-Path, Self-Supervised, Target-Free LiDAR-Camera Extrinsic Calibration Networkcited by 0
- 2026DST-Calib: A Dual-Path, Self-Supervised, Target-Free LiDAR-Camera Extrinsic Calibration Network3 Jan 2026
- 2025Single-Frame Point-Pixel Registration via Supervised Cross-Modal Feature Matching28 Jun 2025
- 2025Environment-Driven Online LiDAR-Camera Extrinsic Calibration2 Feb 2025
- 2024Online,Target-Free LiDAR-Camera Extrinsic Calibration via Cross-Modal Mask Matching28 Apr 2024
- 2022V2XP-ASG: Generating Adversarial Scenes for Vehicle-to-Everything Perception27 Sep 2022