Unbiased Conic Estimation for Distortion-Aware Camera Calibration
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Solution Overview
Problem
Existing camera calibration methods using circular pattern boards suffer from inaccuracies due to distortion, particularly in estimating control points, leading to biased projection models and poor calibration results, especially in cases with nonlinear lens distortion.
Innovation Solution
A method and device using an unbiased conic estimator that calculates the center of a distorted ellipse as a linear combination of moments of the ellipse, allowing accurate camera calibration by expressing the control point in a camera coordinate system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a circular pattern board is used for camera calibration, then the accuracy of observing the control point is improved, but the calibration accuracy deteriorates when camera distortion exists
Solution Approach 1:
The patent introduces an unbiased conic estimator as an intermediary computational method to process the relationship between the circular pattern and its distorted projection. This estimator acts as a mediator that correctly interprets the distorted ellipse parameters to recover the original control point location, eliminating the bias that would otherwise propagate through the calibration process.
Solution Approach 2:
The patent changes the mathematical parameters used to describe the conic section by deriving relationships between the parameters of the distorted ellipse and the original circle. By establishing correct parameter transformations that account for distortion, the method recovers accurate control point positions despite the distorted appearance in the image plane.
2Ease of operation
If traditional calibration algorithms are used with circular patterns, then the process is simple, but the calibration accuracy deteriorates due to distortion bias
Solution Approach 1:
The unbiased conic estimator serves as a specialized intermediary algorithm that corrects the distortion bias in the projection model. It processes the distorted conic parameters and transforms them into accurate control point coordinates, maintaining the simplicity of using circular patterns while eliminating the accuracy deterioration caused by distortion.
3Device complexity
If the center of a distorted ellipse is directly used as the control point, then the calculation is straightforward, but the estimation becomes biased and inaccurate
Solution Approach 1:
The patent introduces an unbiased estimation algorithm as an intermediary computational step between detecting the distorted ellipse and using its center as the control point. This intermediary process corrects the biased center estimation by applying mathematical relationships that account for distortion, transforming the inaccurate direct center into an accurate control point location.
Solution Approach 2:
The method changes the parameter interpretation by establishing correct relationships between the distorted ellipse parameters and the original circular pattern parameters. Instead of directly using the distorted center coordinates, the algorithm transforms the parameters through distortion-aware mathematical relationships to recover the true control point position.
Data Source
AI summary
The present disclosure relates to a method and device for a camera calibration algorithm using an unbiased conic estimator considering distortion, and may be configured to calculate an ellipse in a normalized coordinate system from a circular pattern in a space, express a center of a distorted ellipse in a camera coordinate system as a linear combination of moments of the ellipse, and perform camera calibration from an image of the circular pattern using the center as a control point.