Infrastructure Camera Calibration for Position Deviation Correction
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Solution Overview
Problem
Infrastructure cameras face reduced accuracy in estimating the position of a mobile body due to mechanical deviations caused by external influences, such as camera displacement and illumination changes, which complicates the calculation of positional deviations.
Innovation Solution
A calibration system that includes a storage unit for reference trajectories, an acquisition unit for sequential images, a generation unit for estimated trajectories, a calculation unit for positional deviations, a correction unit for updating landmark positions, and an update unit for transforming two-dimensional image positions to three-dimensional positions, using a position transformation model to improve estimation accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the infrastructure camera is installed to monitor the road, then the position of mobile bodies can be estimated, but mechanical deviations occur due to external influences causing reduced estimation accuracy
Solution Approach 1:
The system performs preliminary calibration by capturing images at multiple known positions before actual operation. These pre-captured images serve as reference data that compensates for future mechanical deviations, allowing the system to maintain accuracy without real-time recalibration.
Solution Approach 2:
The system continuously compares the current camera position with reference positions using captured images and calculated deviation amounts. This feedback mechanism enables automatic correction of position transformation parameters to compensate for mechanical deviations caused by external influences.
2Measurement precision
If calibration is performed frequently to maintain accuracy, then position estimation accuracy improves, but processing load increases
Solution Approach 1:
Instead of performing full calibration frequently, the system performs partial calibration only when necessary by calculating deviation amounts from reference trajectories and updating only the affected position transformation parameters, reducing processing load while maintaining accuracy.
Solution Approach 2:
The system changes calibration from a frequent full-process operation to a selective parameter update process. By calculating positional deviations and updating only the necessary transformation parameters based on actual deviation amounts, the system reduces processing load while maintaining estimation accuracy.
3Measurement precision
If the position transformation model is updated continuously, then the accuracy of transforming two-dimensional image positions to three-dimensional positions improves, but device complexity increases
Solution Approach 1:
The calibration system performs self-calibration by automatically calculating positional deviations from reference trajectories and updating its own position transformation parameters without external intervention, reducing operational complexity while maintaining high transformation accuracy.
Solution Approach 2:
The system creates a virtual reference trajectory by mapping three-dimensional landmark positions to two-dimensional image positions. This copied reference data is then used to calculate deviation amounts and update the position transformation model, simplifying the calibration process while maintaining accuracy.
Data Source
AI summary
A calibration system includes: a storage unit that stores a reference trajectory of a mobile body in an image of a predetermined traffic environment photographed by an imaging sensor and a reference position in the image; an acquisition unit that acquires a plurality of the images of the traffic environment that are sequentially photographed; a generation unit that generates an estimated trajectory of the mobile body based on position information of the mobile body detected from the plurality of the images; a calculation unit that calculates an amount of positional deviation of the imaging sensor based on the reference trajectory and the estimated trajectory; a correction unit that corrects the reference position by using the amount of positional deviation; and an update unit that updates a position transformation model for transforming a two-dimensional position in the image into a three-dimensional position by using the corrected reference position.