AR Goggles Calibration via Sequential Point Illumination
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Solution Overview
Problem
Current methods for calibrating augmented-reality glasses in transportation vehicles require manual alignment of points in real and virtual spaces, which is impractical for users, especially while driving, due to the need for relative measurements and additional sensor systems.
Innovation Solution
A method involving sequential illumination of predefined points in the vehicle's interior by a light source, captured by the glasses' camera, and comparison with known geometry to determine a transformation specification for accurate calibration, allowing unambiguous point assignment without user intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual alignment of points is used for calibration, then measurement precision can be achieved, but ease of operation deteriorates due to requiring user intervention while driving
Solution Approach 1:
The system performs self-calibration by automatically capturing images of sequentially illuminated points and computing transformation specifications without requiring user intervention. The augmented reality glasses autonomously complete the calibration process by capturing images and processing the data to determine the transformation between real and virtual coordinate systems.
Solution Approach 2:
The calibration points are pre-defined in the vehicle interior with known coordinates, and their positions are illuminated sequentially before capture. This preliminary preparation of point positions and sequential illumination eliminates the need for manual alignment during the calibration process, allowing automatic computation of transformation specifications.
2Measurement precision
If additional sensor systems are added for calibration, then measurement precision improves, but device complexity increases
Solution Approach 1:
The existing camera in the augmented reality glasses is used for multiple purposes: both for capturing the calibration points and for the primary augmented reality function. This multi-functional use of the camera eliminates the need for additional dedicated sensor systems for calibration, reducing device complexity while maintaining calibration precision.
Solution Approach 2:
The system uses its own existing camera and processing capabilities to perform calibration, rather than requiring external or additional sensor systems. The augmented reality glasses self-calibrate using their built-in camera to capture sequentially illuminated points and compute transformation specifications.
3Ease of operation
If sequential illumination is used for calibration, then ease of operation improves by eliminating user intervention, but time consumption increases
Solution Approach 1:
The calibration points are illuminated sequentially in a periodic manner, with each point illuminated for a brief period and then the next point illuminated. This sequential periodic illumination allows the camera to capture each point clearly while keeping the total calibration time relatively short, balancing automatic operation with time efficiency.
Solution Approach 2:
The calibration process rushes through the illumination and capture sequence quickly by illuminating each point only briefly and continuously moving to the next point. This rapid sequential process minimizes the total calibration time while still allowing sufficient capture of each illuminated point for accurate transformation computation.
4Productivity
If multiple points are illuminated simultaneously, then calibration speed improves, but measurement precision deteriorates due to ambiguous point assignment
Solution Approach 1:
The calibration process segments the illumination of multiple points into sequential individual point illumination rather than simultaneous illumination. Each point is illuminated one at a time in a defined sequence, allowing unambiguous assignment of captured points to their known coordinates while maintaining relatively fast calibration speed through the sequential process.
Data Source
AI summary
A method, a computer-readable storage medium with instructions, a device, and a system for calibrating a pair of augmented-reality glasses in a transportation vehicle and a transportation vehicle and a pair of augmented-reality glasses suitable for the method. A set of points in an interior of the transportation vehicle is illuminated sequentially. At least a subset of the illuminated points are captured by a camera arranged in the pair of augmented-reality glasses. Through a comparison of the subset of the illuminated points that have been captured by the camera with a known geometry of the set of points, a transformation specification for the pair of augmented-reality glasses is determined.