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Targetless Calibration of Wide-Baseline and Wide-Angle Surround-View Fisheye Cameras Using Cylindrical Projection

Gee Hoon Lee¹, Soon-Yong Park¹

¹School of Electronic and Electrical Engineering, Kyungpook National University, Daegu 41566, Republic of Korea.

Sensors (Basel, Switzerland)

|June 26, 2026

Summary

This summary is machine-generated.

This study introduces a new method for calibrating vehicle fisheye cameras without targets. It uses object detection and depth estimation for accurate surround view monitoring.

Keywords:

autonomous driving cylindrical coordinate system extrinsic calibration monocular depth estimation multi-camera systems wide-baseline fisheye camera

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Area of Science:

Computer Vision
Robotics
Sensor Fusion

Background:

Surround view monitoring systems in vehicles rely on accurate camera calibration.
Traditional methods often require artificial targets, limiting online application.
Wide-baseline and wide-angle fisheye cameras present unique calibration challenges.

Purpose of the Study:

To develop a novel targetless extrinsic calibration method for fisheye cameras on driving vehicles.
To enable online calibration for surround view monitoring systems.
To improve calibration accuracy under challenging conditions like wide baselines and low frame rates.

Main Methods:

Fisheye images are transformed into a cylindrical coordinate system.
State-of-the-art object detection and monocular depth estimation are applied.
3D point clouds are reconstructed from matched vehicle instances across views.
Depth scaling and joint optimization are used for accurate cross-view alignment.

Main Results:

The proposed method achieves higher accuracy than existing approaches (COLMAP, DUSt3R).
Effective calibration was demonstrated on both real-world and synthetic datasets.
The method successfully calibrates cameras without requiring artificial targets.
Accurate extrinsic calibration was achieved even under challenging conditions.

Conclusions:

The novel targetless method provides accurate extrinsic calibration for vehicle fisheye cameras.
This approach is suitable for online calibration in surround view monitoring.
It overcomes limitations of traditional target-based methods and improves robustness.