Point-Symmetric Camera Calibration Patterns
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Solution Overview
Problem
Conventional camera calibration methods using black and white patterns face challenges such as partial occlusion, rotation, and perspective issues, which affect the accuracy and robustness of calibration data.
Innovation Solution
The use of point-symmetric regions and patterns, which are invariant to rotation and perspective, allows for robust and precise detection and localization of symmetry centers, even under partial occlusion. These patterns utilize a larger portion of their two-dimensional surface for information, enhancing accuracy and reducing the risk of false detections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If conventional black and white patterns (checkerboard, circles) are used for camera calibration, then the calibration process is simple to implement, but the accuracy and robustness deteriorate under partial occlusion, rotation, and perspective changes
Solution Approach 1:
The patent applies point-symmetric patterns instead of conventional asymmetric checkerboard or circle patterns. The point symmetry creates a center of symmetry that remains detectable under partial occlusion and perspective changes, while the asymmetric arrangement of symmetric elements around the center provides rotation invariance. This resolves the contradiction by maintaining simple implementation through symmetric geometry while achieving robustness under challenging conditions.
Solution Approach 2:
The patent changes the fundamental geometric parameter from line-based or edge-based features (checkerboard corners, circle edges) to point-symmetric region centers. This parameter change enables the calibration target to maintain its identification features under partial occlusion and perspective transformation, as the center of symmetry is a stable geometric invariant that can be detected even when parts of the pattern are obscured or distorted.
2Device complexity
If conventional black and white patterns are used, then the pattern design is simple, but the measurement precision deteriorates due to limited information content and sensitivity to occlusion
Solution Approach 1:
The patent transitions from one-dimensional line-based features (checkerboard edges) to two-dimensional point-symmetric regions. This dimensional expansion allows the entire surface area of each region to contribute to the detection of the center of symmetry, significantly increasing the information content and measurement precision. The center of symmetry can be localized with sub-pixel accuracy by analyzing the distribution of symmetric points across the entire region, rather than relying on edge intersections.
Solution Approach 2:
The patent merges multiple information sources within each point-symmetric region by combining the positions of all symmetric point pairs to determine the center of symmetry. This merging of information from the entire region surface, rather than relying on specific edge or corner features, enhances the precision and robustness of the center localization, making it resistant to partial occlusion and noise.
3Device complexity
If conventional calibration targets are used, then the target structure is simple, but the reliability deteriorates due to false detections and sensitivity to extreme brightness regions
Solution Approach 1:
The patent applies different gray value relationships to different parts of the point-symmetric regions. Specifically, symmetric point pairs have inverted gray value relationships (one light, one dark), which creates a distinctive local quality that is invariant to overall brightness changes. This local quality differentiation enables reliable detection of the center of symmetry while avoiding false detections from extreme brightness regions, as the symmetric structure itself provides the detection cue rather than absolute brightness values.
Data Source
AI summary
A method for providing calibration data for calibrating a camera. The method includes reading in image data provided by the camera from the camera. The image data represent a camera image of at least one predefined point-symmetric region. The method also includes determining at least one center of symmetry of the at least one point-symmetric region using the image data and a determination rule, performing a comparison of a position of the center of symmetry in the camera image with a predefined position of a reference center of symmetry in a reference image in order to determine a positional deviation between the center of symmetry and the reference center of symmetry, and ascertaining displacement information for at least a subset of pixels of the camera image relative to corresponding pixels of the reference image, using the positional deviation. The calibration data are provided using the displacement information.