Offline IMU-Camera Calibration for Accurate Motion Tracking
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Solution Overview
Problem
Existing motion-tracking devices suffer from inaccuracies due to sensor imperfections and environmental changes, which affect the accuracy of motion tracking in augmented and virtual reality experiences.
Innovation Solution
A method for calibrating motion-tracking devices during periods of inactivity by adjusting calibration parameters for the IMU and camera intrinsics and extrinsics, using data collected during active use and optimized during idle times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If calibration is performed during active use, then measurement precision can be improved, but user experience and ease of operation deteriorate due to interruptions
Solution Approach 1:
The system performs calibration during idle periods before the next active use session begins. Calibration parameters are computed in advance using data collected during the idle period, so that when the user resumes active use, the device is already calibrated and ready to provide accurate motion tracking without interrupting the user experience.
2Measurement precision
If calibration parameters are frequently updated, then measurement precision improves, but device complexity and processing time increase
Solution Approach 1:
The system performs calibration periodically during idle periods rather than continuously or frequently during active use. This periodic approach allows the device to maintain accurate calibration parameters while avoiding the complexity and processing overhead of frequent calibration computations, as calibration is only performed when the device is not being actively used.
3Measurement precision
If calibration data is collected during active use, then measurement precision improves, but loss of time occurs due to processing during user sessions
Solution Approach 1:
The system collects calibration data and computes calibration parameters during idle periods before active use begins. This preliminary action ensures that all data processing and calibration computations are completed in advance, so that during active use sessions, no time is lost to processing - the device can immediately provide accurate motion tracking with pre-computed calibration parameters.
Data Source
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AI summary
Calibration parameters of an IMU and a camera of a motion-tracking device can be used to compensate for errors in a motion-tracking process. The calibration parameters may be determined by an optimization algorithm run while the motion-tracking device is idle (i.e., offline). Data for the calibration can be collected while the motion-tracking device is in use (i.e., online) and accumulated in a database. When the motion-tracking device is not in use (i.e., idle), the data may be recalled from the database and used in an optimization process, which iteratively adjusts the calibration parameters until correct estimates are determined. The resulting set of calibration parameters may be used for a subsequent motion-tracking process after the motion-tracking device returns to use. This process may be repeated so that the calibration parameters remain accurate even as the IMU and the camera change over time.