Binocular Display Misalignment Correction in ER Systems
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Solution Overview
Problem
Extended reality (ER) systems face challenges with display misalignment, leading to user discomfort and hologram misplacement, particularly due to horizontal and vertical angular misalignments, which are not effectively addressed in all ER devices, especially those without dedicated sensors like IMUs.
Innovation Solution
The implementation of a method to detect user activity and trigger correction algorithms to correct binocular image misalignments, using hand tracking input to determine when to prioritize fast or slow corrections based on user interaction, ensuring accurate or uninterrupted performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If a correction algorithm is continuously executed to correct binocular image misalignment, then manufacturing precision of hologram display is improved, but use of energy and processing resources increases
Solution Approach 1:
The correction algorithm is executed periodically based on detected user activity levels rather than continuously. When user activity exceeds a threshold, the system triggers correction execution; when activity remains below the threshold, execution is deferred. This periodic execution based on activity triggers reduces energy consumption while maintaining acceptable alignment precision during active use.
Solution Approach 2:
The system uses its own operational state (user activity level) to automatically control the correction algorithm execution. By monitoring user activity and self-regulating when to apply corrections, the system optimizes resource usage without external intervention, balancing precision requirements with energy conservation.
2Use of energy by moving object
If correction algorithm execution is delayed to save processing resources, then use of energy is reduced, but manufacturing precision of hologram display deteriorates
Solution Approach 1:
The system implements periodic correction execution triggered by user activity thresholds. Instead of continuous execution, corrections are applied at intervals determined by activity detection, reducing energy consumption while ensuring precision is maintained during periods when user interaction indicates alignment issues may affect performance.
Solution Approach 2:
The system performs preliminary detection of user activity levels before executing the correction algorithm. By anticipating when corrections will be needed based on activity patterns, the system can prepare and execute corrections proactively during active periods, preventing precision deterioration while conserving energy during inactive periods.
3Manufacturing precision
If fast correction algorithm is used during high user activity, then manufacturing precision is improved, but productivity of other processing tasks decreases
Solution Approach 1:
The system uses periodic execution triggered by user activity thresholds to balance fast correction with overall productivity. During high-activity periods when precision is critical, fast correction algorithms are invoked. During low-activity periods, correction execution is deferred or slowed, allowing other processing tasks to maintain higher throughput and overall system productivity.
4Manufacturing precision
If continuous correction execution is performed, then manufacturing precision is maintained, but device complexity increases
Solution Approach 1:
The system implements a simplified control mechanism that uses periodic activity-based triggering instead of continuous complex control logic. By monitoring user activity levels and triggering corrections only when thresholds are exceeded, the system maintains precision during active use while reducing overall control complexity and computational burden compared to continuous execution schemes.
Data Source
AI summary
Techniques for triggering a correction to a binocular image misalignment in an ER system are disclosed. Triggering this correction is based on detected activity in a scene in which the ER system is operating. A first hologram is displayed. User activity is detected, but this activity is below a threshold level. A first correction algorithm is selected and is designed to achieve uninterrupted performance with respect to the first hologram. The first correction algorithm is triggered, resulting in correction of binocular image misalignment. Subsequently, second user activity is detected. This second user activity is associated with a second hologram. A second correction algorithm is selected and is designed to achieve accurate performance with respect to the second hologram. The second correction algorithm is executed, resulting in correction of the binocular image misalignment.


