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Equidistant fish-eye calibration and rectification by vanishing point extraction.

Ciarán Hughes¹, Patrick Denny, Martin Glavin

¹Vision Technology and Expertise Group, Valeo Vision Systems, Tuam, Co. Galway, Ireland. ciaran.hughes@valeo.com

IEEE Transactions on Pattern Analysis and Machine Intelligence

|August 25, 2010

Summary

This study presents a photogrammetric method for calibrating fish-eye cameras. The technique accurately estimates camera parameters for rectified image generation, improving scene viewing applications.

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Area of Science:

Computer Vision
Photogrammetry
Optical Engineering

Background:

Fish-eye cameras offer a wide field of view but introduce significant lens distortion.
Accurate camera calibration is crucial for reliable 3D scene reconstruction and analysis.
Existing methods may struggle with the extreme distortions inherent in fish-eye lenses.

Purpose of the Study:

To develop a robust photogrammetric method for estimating intrinsic and extrinsic parameters of fish-eye cameras.
To leverage equidistance perspective properties and vanishing point estimation for improved calibration accuracy.
To provide a method for generating rectified images suitable for various scene viewing applications.

Main Methods:

Utilized photogrammetry principles for camera parameter estimation.
Employed equidistance projection properties, specifically vanishing point estimation, for calibration.
Calibrated using a checkerboard pattern to determine intrinsic (optical center, lensing parameter) and extrinsic (rotations) parameters.

Main Results:

Successfully estimated intrinsic parameters, including the optical center and fish-eye lensing parameter.
Accurately determined extrinsic parameters, specifically the rotations relative to the calibration diagram.
The method facilitates the generation of rectified images from fish-eye camera data.

Conclusions:

The proposed photogrammetric method provides an effective approach for calibrating fish-eye cameras.
Vanishing point estimation based on equidistance perspective is a viable technique for handling fish-eye lens distortions.
The generated rectified images enhance the usability of fish-eye camera data in scene viewing applications.