Automated IPD Determination via 3D Image Feedback
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Solution Overview
Problem
Current methods for determining interpupillary distance (IPD) are user-dependent and may cause dizziness if the optical device axis is not aligned with the user's gaze, especially when displaying three-dimensional (3D) images, as they rely on physical measurements that can vary between individuals.
Innovation Solution
A method and apparatus that generate test 3D images for various candidate IPDs based on eye coordinates, allowing users to provide feedback on the clarity of these images, which are then used to calculate and adjust the final IPD by updating candidate IPDs based on user feedback, ensuring accurate alignment and reducing dizziness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a physical measuring device is used to determine IPD, then the measurement can be performed, but the measurement precision varies based on user dependency and operator technique
Solution Approach 1:
The patent replaces mechanical measurement devices (rulers, physical calipers) with an optical-based automated system that captures eye images and calculates IPD through coordinate detection and 3D spatial computation. This substitution eliminates manual measurement errors and user dependency while maintaining measurement capability.
Solution Approach 2:
The system performs self-measurement by automatically capturing eye images, detecting pupil coordinates, calculating 3D eye positions, and determining IPD without requiring external operators or manual intervention. The device measures itself and the user's IPD through automated image processing algorithms.
2Measurement precision
If candidate IPDs are tested with multiple test images, then the accuracy of final IPD determination is improved, but the time required for IPD determination increases
Solution Approach 1:
The system pre-calculates multiple candidate IPD values based on initial eye coordinate detection before presenting test images to the user. This preliminary preparation allows for efficient comparison and selection of the most accurate IPD without requiring extensive real-time computation during the testing phase.
Solution Approach 2:
The system dynamically adjusts the testing process by receiving user feedback on test images and iteratively refining candidate IPD selections. The number of test iterations can be adapted based on convergence criteria, allowing the system to balance accuracy requirements with time constraints by stopping when sufficient precision is achieved.
Data Source
AI summary
A method and apparatus for determining an interpupillary distance (IPD) are provided. To determine an IPD of a user, three-dimensional (3D) images for candidate IPDs may be generated, and user feedback on the 3D images may be received. A final IPD may be determined based on the user feedback.