Geometric Calibration of Images Using Homography Extrapolation
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Solution Overview
Problem
Existing methods for geometric alignment of images from cameras with different orientations require significant overlapping fields of view, leading to inaccuracies in extrinsic parameter estimation due to noise and limited resolution, especially when the overlap is minimal or absent.
Innovation Solution
A direct homography estimation method that extrapolates missing pattern points beyond the image section, allowing for accurate calibration without the need for field of view overlap, using a feature recognition unit, homography calculation unit, and feature extrapolation unit to determine the geometric calibration of images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If significant overlapping field of view is used between cameras, then robustness and accuracy of extrinsic parameter estimation is improved, but the adaptability to minimal overlap scenarios deteriorates
Solution Approach 1:
The patent performs preliminary geometric calibration of individual cameras using a calibration target before the actual imaging process. This preliminary calibration establishes accurate intrinsic parameters and distortion models for each camera, enabling robust extrinsic parameter estimation even when field of view overlap is minimal. The calibration pattern is captured in advance to create reference data that compensates for limited overlap during operation.
Solution Approach 2:
The patent introduces a calibration target with a known geometric pattern as an intermediary object that mediates between multiple cameras. This calibration target serves as a common reference frame that all cameras can observe and relate to, enabling accurate relative pose estimation without requiring direct overlap between camera fields of view. The calibration target acts as an intermediate coordinate system that connects different camera views.
2Productivity
If minimal overlapping field of view is used between cameras, then the number of necessary cameras is reduced, but the accuracy of extrinsic parameter estimation deteriorates
Solution Approach 1:
The system performs preliminary calibration of each camera individually using a calibration target before capturing images of the scene. This preliminary action establishes accurate intrinsic parameters and distortion characteristics for each camera. When images with minimal overlap are captured, the pre-calibrated parameters enable accurate extrinsic estimation through the calibration target's known geometry, compensating for the limited overlap.
Solution Approach 2:
The patent changes the approach from direct overlap-based extrinsic estimation to a two-stage process: first calibrating intrinsic parameters using a calibration target, then using those calibrated parameters to estimate extrinsic parameters even with minimal overlap. This parameter transformation enables accurate results with fewer cameras by decoupling intrinsic and extrinsic calibration requirements.
3Device complexity
If field of view overlap is minimal or absent, then camera system complexity is reduced, but the reliability of geometric calibration deteriorates
Solution Approach 1:
The calibration target with known geometric pattern serves as an intermediary reference that all cameras can independently observe and relate to. This intermediary provides a common coordinate system that enables reliable geometric calibration without requiring direct field of view overlap between cameras. Each camera calibrates its position and orientation relative to the calibration target, and the target mediates the relationship between cameras.
Solution Approach 2:
The system performs preliminary calibration using the calibration target to establish accurate intrinsic parameters and distortion models before actual imaging. This preliminary action ensures reliable geometric calibration by separating the intrinsic calibration (done with the target) from the extrinsic calibration (done with scene images), allowing minimal or no field of view overlap during operation while maintaining high reliability.
Data Source
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AI summary
An image processing device (132) for performing a geometric calibration of at least a first image and a second image is provided. The image processing device (132) comprises a feature recognition unit (140) adapted to detect features of a calibration pattern. A homography calculation unit is adapted to determine a first homography of the first image and the calibration target and determine a second homography of the second image and the calibration target. A feature extrapolation unit is adapted to extrapolate further features of the calibration pattern. A geometry calculation unit (142) is adapted to determine a third homography between the first image and the second image based upon the features of the known calibration pattern within the first and second image, the extrapolated features of the known calibration pattern.