Scanning Retinal Imaging for Eye Tracker Characterization
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Solution Overview
Problem
Conventional eye tracking systems face limitations due to the quality of optical paths and limited modeling of eye features across the human population, necessitating a source of 'ground truth' eye tracking data for improved performance, especially in head-mounted display systems for virtual, augmented, and mixed reality applications.
Innovation Solution
An eye tracker characterization system that includes a scanning retinal imaging unit and a controller, which scans light across a retinal region, detects reflected light, and calculates differences between eye tracking information from an eye tracking unit and corresponding parameters from the scanning retinal imaging unit to characterize the eye tracking data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional eye tracking systems track features on the anterior surface of the eye, then the system structure remains simple, but the measurement precision is limited by optical path quality and modeling constraints
Solution Approach 1:
The patent introduces a scanning retinal imaging system as an intermediary device that provides ground truth retinal position data. This mediator allows comparison between eye tracker measurements and actual retinal positions, enabling precision characterization without requiring the eye tracker itself to directly measure retinal position, thus resolving the contradiction between measurement precision and device complexity
Solution Approach 2:
The patent creates a copy of the eye tracking measurement process using a scanning retinal imaging system that independently measures retinal position. This copy serves as ground truth data for validating and characterizing the original eye tracker's precision, allowing high-precision measurement without adding complexity to the operational eye tracking system
2Reliability
If conventional eye tracking systems use limited modeling of eye features, then the device complexity remains low, but the reliability of eye tracking data is reduced
Solution Approach 1:
The patent implements a feedback mechanism where the scanning retinal imaging system continuously provides ground truth retinal position data to characterize eye tracker performance. This feedback loop enables ongoing validation and improvement of eye tracking reliability through comparison with actual retinal positions, enhancing data reliability without requiring complex internal modeling within the eye tracker itself
Solution Approach 2:
The scanning retinal imaging system serves as an intermediary that provides independent verification of eye tracking reliability. By mediating between the eye tracker and ground truth retinal positions, it enables reliability assessment and improvement without requiring the eye tracker to incorporate complex modeling algorithms
3Measurement precision
If a scanning retinal imaging system is introduced to provide ground truth data, then measurement precision improves, but device complexity increases
Solution Approach 1:
The patent segments the overall system into two independent parts: the operational eye tracking system and the separate scanning retinal imaging characterization system. This segmentation allows the characterization system to provide high-precision ground truth data independently, improving measurement precision without requiring integration that would increase overall system complexity
Solution Approach 2:
The scanning retinal imaging system creates a copied measurement of retinal position that serves as ground truth. This copy enables precise characterization of eye tracking performance without the operational eye tracker needing to be modified or made more complex, resolving the contradiction between precision improvement and complexity increase
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
Provides accurate characterization of eye tracking information, serving as a 'ground truth' for eye tracking systems, enhancing their performance and reliability in head-mounted displays by improving data quality and overcoming previous limitations.
Implementation Method 1
a scanning optics assembly and a detector. The scanning optics assembly scans light in a first band across a retinal region of an eye of a user
Implementation Method 2
The scanning optics assembly scans light in a first band across a retinal region of an eye of a user
Implementation Method 3
The detector detects the scanned light reflected from the retinal region
Data Source
AI summary
An eye tracker characterization system comprising a scanning retinal imaging unit and a controller. The scanning retinal imaging unit characterizes eye tracking information determined by an eye tracking unit under test. The scanning retinal imaging unit includes a scanning optics assembly and a detector. The scanning optics assembly scans light in a first band across a retinal region of an eye of a user. The detector detects the scanned light reflected from the retinal region. The controller selects eye tracking information received from the eye tracking unit under test and corresponding eye tracking parameters received from the scanning retinal imaging unit. The controller calculates differences between the selected eye tracking information and the corresponding selected eye tracking parameters, and characterizes the selected eye tracking information based on the calculated differences.