Multisensor Imaging Calibration for In-Procedure Heat Drift
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Solution Overview
Problem
Multicamera imaging systems experience calibration drift due to environmental factors such as heat, leading to reduced accuracy and repeatability over time, which is difficult to detect during normal operation.
Innovation Solution
A method and system for updating the calibration of an imaging system during an imaging procedure by capturing image data of a rigid body with known geometry, determining calibration drift, and adjusting the calibration based on this data to maintain accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the imaging system operates continuously under environmental factors, then productivity is improved, but calibration accuracy deteriorates due to drift
Solution Approach 1:
The system implements continuous monitoring of calibration quality metrics during operation and automatically triggers recalibration when drift exceeds thresholds, creating a closed-loop feedback mechanism that maintains accuracy while enabling continuous productivity
Solution Approach 2:
The system performs preliminary calibration using a rigid body target before operation and periodically during operation to prevent drift accumulation, ensuring calibration accuracy is maintained proactively rather than reactively
2Measurement precision
If calibration is performed frequently to maintain accuracy, then measurement precision is improved, but loss of time increases due to calibration interruptions
Solution Approach 1:
Instead of performing full recalibration routines, the system uses partial calibration updates based on monitored drift metrics, applying only the necessary adjustments to maintain accuracy while minimizing time loss
Solution Approach 2:
The system automatically monitors its own calibration quality and performs self-calibration when needed, eliminating the need for manual intervention and reducing time loss associated with user-discretion-based calibration checks
3Device complexity
If manual calibration checking is left to user discretion, then device complexity is reduced, but reliability deteriorates due to undetected calibration drift
Solution Approach 1:
The system automatically computes calibration quality metrics by comparing known rigid body geometry with captured images and provides feedback on calibration status, ensuring reliable detection of drift without adding complex manual monitoring procedures
Solution Approach 2:
The imaging system autonomously monitors its own calibration quality and triggers recalibration when drift is detected, making the system self- verifying without requiring external user intervention or complex external monitoring equipment
Data Source
AI summary
Methods and systems for calibrating an imaging system having a plurality of sensors are disclosed herein. In some embodiments, a method includes initially calibrating the imaging system, operating the imaging system during an imaging procedure, and then updating the calibration during the imaging procedure to account for degradation of the initial calibration due to environmental factors, such as heat. The method of updating the calibration can include capturing image data of a rigid body having a known geometry with the sensors and determining that the calibration has drifted for a problematic one of the sensors based on the captured image data. After determining the problematic one of the sensors, the method can include updating the calibration of the problematic one of the sensors based on the captured image data.