Pre-Distorted Camera Targets for Wide-Angle Alignment Accuracy
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Solution Overview
Problem
Current digital camera systems face challenges in alignment, particularly with wide-angle cameras using flat target boards and collimator targets, leading to inaccurate lens center estimation and calibration due to excessive distortion and alignment tolerance issues.
Innovation Solution
The use of pre-distorted targets that project specific shapes onto the camera lenses, allowing for precise alignment by manipulating the lenses to match desired shapes in the images, facilitating accurate calibration and determination of principal points and effective focal lengths.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If flat target boards and collimator targets are used for camera alignment, then the alignment process can be performed, but excessive distortion occurs in wide-angle cameras leading to inaccurate alignment
Solution Approach 1:
The patent applies preliminary action by pre-distorting the target pattern before it is displayed to the camera. The distortion correction data is prepared in advance based on the camera's lens characteristics, so that when the camera captures the target, the pre-applied distortion compensation results in an undistorted appearance, enabling accurate alignment measurement even with wide-angle lenses that inherently introduce distortion
Solution Approach 2:
The patent changes the parameters of the target pattern by applying distortion correction data that is specific to each camera's lens characteristics. The system adjusts the geometric parameters of the target pattern (such as the arrangement and shape of feature points) based on the camera's field of view and distortion characteristics, transforming a standard undistorted pattern into a pre-distorted pattern that compensates for the camera's optical distortion
2Measurement precision
If standard alignment targets are used, then alignment can be performed, but alignment tolerances lead to inaccurate estimation of lens center
Solution Approach 1:
The patent applies local quality by designing the target pattern with non-uniform distribution of feature points. The density and arrangement of feature points are locally optimized based on the distortion characteristics at different regions of the camera's field of view. Areas with higher distortion or greater sensitivity to alignment errors have higher density or strategically positioned feature points, while less critical areas have lower density, thereby improving lens center estimation accuracy without uniformly increasing the entire target's complexity
Solution Approach 2:
The system incorporates feedback by using the captured distorted target image to calculate alignment errors, then iteratively adjusting the lens position and the distortion correction parameters. The process compares the actual captured feature point positions with the expected positions from the pre-distorted target pattern, uses the discrepancy as feedback to refine the alignment, and repeats until convergence, thereby compensating for alignment tolerances
3Area of stationary object
If wide-angle cameras are used, then broader field of view is achieved, but distortion increases making accurate calibration difficult
Solution Approach 1:
The patent applies preliminary action by pre-calculating and pre-applying distortion compensation specific to wide-angle lens characteristics. The system generates distortion correction data in advance that is tailored to the wide-angle camera's optical properties, so that when the camera captures the pre-distorted target, the compensation already accounts for the wide-angle distortion, enabling accurate calibration despite the broad field of view
Solution Approach 2:
The patent changes the parameters of the target pattern by applying distortion correction data that is specific to each camera's lens characteristics. The system adjusts the geometric parameters of the target pattern (such as the arrangement and shape of feature points) based on the camera's field of view and distortion characteristics, transforming a standard undistorted pattern into a pre-distorted pattern that compensates for the camera's optical distortion
Data Source
AI summary
Provided are systems and methods for camera alignment using pre-distorted targets. Some methods described include selecting a configuration of shapes, and determining targets by pre-distorting the shapes according to the inverse of the distortion function of the lens system to be aligned. Images of pre-distorted targets are then compared to the original configuration of shapes, to perform camera alignment. Alignment is thus accomplished in simpler and more accurate manner. Systems and computer program products are also provided.