Mono Visual-Tracking Camera Recalibration for Thermal Drift
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Solution Overview
Problem
Existing visual tracking systems face challenges in accurately calibrating camera intrinsic parameters due to thermal distortions caused by heat generated by cameras and other components, leading to misalignment of detected and projected features, especially in augmented and virtual reality devices.
Innovation Solution
A method for recalibrating camera intrinsic parameters by detecting thermal changes and generating a temperature-based distortion model, involving a series of interactive operations to adjust feature points from the central to the border area of the camera lens, using a visual-inertial tracking system to correct features based on temperature-specific intrinsic parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If factory calibration parameters are used, then the system is simple to operate, but the measurement precision deteriorates under different thermal conditions
Solution Approach 1:
The system dynamically adjusts camera intrinsic parameters based on detected temperature changes. When the camera temperature exceeds the factory calibration temperature by a threshold, the system triggers a recalibration process that modifies focal length, principal point, and distortion coefficients to compensate for thermal expansion and lens deformation, thereby maintaining measurement precision under varying thermal conditions
Solution Approach 2:
The system performs self-calibration by automatically detecting temperature changes and executing recalibration procedures without requiring external intervention. The visual-inertial tracking system uses detected feature points and inertial sensor data to autonomously compute updated intrinsic parameters, enabling the system to adapt to thermal conditions independently
2Measurement precision
If interactive recalibration operations are performed, then the measurement precision is improved, but the device complexity increases
Solution Approach 1:
The system implements a feedback mechanism where temperature sensors continuously monitor camera temperature, and when thermal drift exceeds a threshold, the system automatically initiates recalibration. The visual-inertial system provides feedback through detected feature points and pose estimates, allowing the system to iteratively refine intrinsic parameters until convergence, thereby achieving high precision through controlled complexity
Solution Approach 2:
The calibration system transitions from static factory calibration to dynamic adaptive calibration. The system continuously monitors temperature and automatically adjusts intrinsic parameters in real-time based on thermal conditions, transforming the calibration process from a one-time setup to an ongoing adaptive process that maintains precision without permanent complexity
3Measurement precision
If temperature-based distortion modeling is implemented, then the measurement precision is improved, but the use of energy increases
Solution Approach 1:
Instead of continuous recalibration, the system performs calibration periodically based on temperature threshold detection. The system monitors temperature continuously but only triggers recalibration when the temperature change exceeds a predefined threshold, reducing unnecessary computational operations and energy consumption while maintaining measurement precision during significant thermal drift
Solution Approach 2:
The system performs preliminary temperature monitoring and threshold checking before initiating full recalibration. By detecting temperature changes in advance and only triggering recalibration when necessary, the system prepares for energy-intensive operations only when required, optimizing the balance between measurement precision and energy consumption
Data Source
AI summary
A method for adjusting camera intrinsic parameters of a single camera visual tracking device is described. In one aspect, a method includes accessing a temperature of a camera of the visual tracking system, detecting that the temperature of the camera exceeds a threshold, in response identifying one or more feature points that are located in a central region of an initial image, generating a graphical user interface element that instructs a user of the visual tracking system to move the visual tracking system towards a border region of the initial image, and determining intrinsic parameters of the camera based on matching pairs of the one or more detected feature points in the border region and one or more projected feature points in the border region.