Camera Calibration Using Angle-of-View Parameters
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Solution Overview
Problem
Conventional camera calibration methods face challenges in accurately determining camera parameters, especially for cameras with large angles of view, due to distortion aberrations and pupil aberrations, which affect the precision of principal ray modeling and image correction.
Innovation Solution
A calibration device and method that utilize a camera model fitting process, incorporating distortion and pupil aberration models, to calculate camera parameters by transforming world coordinates into projected coordinates and optimizing coefficients using linear least squares methods, allowing for accurate representation of principal rays and image correction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional camera calibration methods are used, then calibration can be performed, but accuracy deteriorates for cameras with large angles of view due to distortion aberrations and pupil aberrations
Solution Approach 1:
The patent introduces new parameters (αu, αv) representing the angles of view of the principal rays in the u and v directions, respectively. By changing the parameterization approach from traditional distortion coefficients to angle-of-view parameters, the model can accurately represent both small and large angle cameras. This parameter transformation allows the camera model to adapt to different angle of view ranges while maintaining calibration accuracy.
Solution Approach 2:
The patent employs an iterative optimization process that dynamically adjusts the camera parameters. The calibration procedure repeatedly refines the parameters (αu, αv, u0, v0, and distortion coefficients) by minimizing the reprojection error between observed and predicted feature point positions. This dynamic optimization enables the model to converge to accurate parameters regardless of the initial angle of view magnitude.
2Measurement precision
If complex distortion models are used to improve accuracy, then measurement precision improves, but computational time increases
Solution Approach 1:
The patent transforms the complex nonlinear distortion model into a more computationally efficient parameterization using angle-of-view parameters (αu, αv). This change allows the use of efficient optimization algorithms while maintaining high accuracy. The new parameterization reduces the computational burden compared to traditional high-order distortion models by providing a more direct geometric interpretation of the principal ray directions.
Solution Approach 2:
The patent replaces iterative nonlinear optimization with a hybrid approach that combines analytical solutions with iterative refinement. By deriving the relationship between pixel coordinates and principal ray angles analytically, the method reduces the reliance on purely numerical optimization, thereby decreasing computational time while preserving measurement precision.
Data Source
AI summary
Provided is a calibration device for an optical device including a two-dimensional image conversion element having a plurality of pixels and including an optical system that forms an image-forming relationship between the image conversion element and a three-dimensional world coordinate space, the calibration device including: a computer, wherein the computer is configured to: obtain calibration data representing the correspondence between two-dimensional pixel coordinates of the image conversion element and three-dimensional world coordinates of the world coordinate space; and fit a camera model representing the direction of a principal ray in the world coordinate space, corresponding to the pixel coordinates, as a function of the pixel coordinates, to the calibration data obtained, thereby calculating parameters of the camera model.