Camera Calibration Two-Stage Refinement
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Solution Overview
Problem
Existing camera calibration methods require dedicated physical components or restrict the camera's use during calibration, and real-time calibration algorithms like SLAM may not provide accurate and stable calibration data due to incremental calculations.
Innovation Solution
A method involving two calibration stages: a real-time initial calibration for each frame and a non-real-time refined calibration for selected frames, using historical calibration data to improve accuracy and correct incremental errors, with separate units for incremental and refined calculations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If real-time calibration algorithms like SLAM are used, then calibration speed is improved, but calibration accuracy deteriorates due to incremental calculations
Solution Approach 1:
The calibration process is segmented into two distinct stages: a first calibration stage that performs real-time incremental calibration for each frame to maintain speed, and a second calibration stage that performs refined non-real-time calibration for selected frames to improve accuracy. This segmentation allows each stage to optimize for its specific performance requirement.
Solution Approach 2:
The first calibration stage performs preliminary calibration calculations for all frames in advance, providing initial calibration data that is then used as a foundation for the second calibration stage. This preliminary action enables the refined calibration to build upon existing results rather than starting from scratch.
2Measurement precision
If dedicated physical calibration components are used, then calibration accuracy is improved, but device complexity and operational restriction worsen
Solution Approach 1:
The camera system performs self-calibration using its own captured images and the known geometry of calibration patterns without requiring external dedicated calibration equipment. The system uses the calibration pattern images captured by the camera itself to compute calibration parameters, eliminating the need for separate calibration devices.
Solution Approach 2:
The camera system serves multiple functions: it performs both image capture and self-calibration using the same hardware. The calibration pattern recognition and parameter calculation are integrated into the existing camera processing pipeline, making the system multi-functional without adding separate dedicated calibration components.
Data Source
AI summary
A method of calibrating a camera performs a first calibration for frames of a sequence captured by the camera to calculate for those frames first calibration data for a set of one or more camera parameters; performs, for selected frames of the sequence, a second calibration to calculate second calibration data for the selected frames in dependence on the first calibration data for those frames; and uses the second calibration data in the first calibration performed for subsequent frames of the sequence.