Prescription Glasses Lens Power Estimation for Accurate HMD Eye Tracking
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Solution Overview
Problem
Existing eye tracking systems in head-mounted displays (HMDs) for virtual reality (VR), augmented reality (AR), and mixed reality (MR) applications are impaired by the presence of prescription glasses, which introduce distortion in eye images, affecting the accuracy of gaze direction estimation.
Innovation Solution
A method and system for estimating the strength of prescription glasses using illuminators, cameras, and computer analysis to determine lens power by analyzing reflections, employing techniques such as base curve rules, curvature regressors, and machine learning to improve eye tracking accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If prescription glasses are worn by users, then vision correction is achieved, but distortion in eye images is introduced, affecting eye tracking accuracy
Solution Approach 1:
The system performs preliminary action by estimating the prescription strength of the user's glasses before conducting eye tracking. The eye tracking system captures images of the glasses and uses image processing to determine lens power and curvature. This preliminary estimation allows the system to pre-compensate for distortion effects in subsequent eye tracking measurements, thereby maintaining accuracy despite the presence of prescription glasses.
2Measurement precision
If distortion compensation is performed without knowing glasses parameters, then eye tracking accuracy is maintained, but the system complexity increases
Solution Approach 1:
The eye tracking system performs self-service by automatically capturing images of the user's glasses and estimating their prescription strength without requiring manual input from the user or external information. The system uses its own imaging resources to detect lens characteristics and automatically compensates for distortion, thereby maintaining accuracy while avoiding the complexity of additional sensors or manual configuration interfaces.
Solution Approach 2:
The system replaces complex mechanical or manual methods of determining glasses parameters with optical imaging and computational analysis. Instead of using physical measurements or user input, the system uses cameras to capture images of the glasses and applies image processing algorithms to estimate lens power and curvature, thereby reducing system complexity while maintaining measurement precision.
3Device complexity
If traditional eye tracking methods are used with prescription glasses, then the system remains simple, but gaze mapping accuracy is impaired
Solution Approach 1:
The system applies parameter changes by modifying the eye tracking algorithm to account for the optical parameters of prescription glasses. Based on the estimated lens power and curvature, the system adjusts the mapping between image coordinates and world coordinates, correcting for distortion effects. This allows the system to maintain simplicity while significantly improving gaze mapping accuracy for users wearing prescription glasses.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances eye tracking performance by providing more accurate gaze mapping and entrance pupil position estimates, leading to an improved user experience in VR, AR, and MR applications.
Implementation Method 1
illuminating a user's eyes and prescription glasses using illuminators
Implementation Method 2
capturing images of the eyes, the prescription glasses, and reflections on the prescription glasses
Data Source
AI summary
A method for estimating the strength of prescription glasses for a user of a head-mounted display is disclosed. The method involves illuminating a user's eyes and prescription glasses using illuminators, capturing images of the eyes, the prescription glasses, and reflections on the prescription glasses using at least one camera, and determining the power of lenses of the prescription glasses by analyzing the reflections. The method can be used to improve the user experience in virtual reality, augmented reality, and mixed reality applications by accounting for the user's prescription glasses.