Retinal Projection Display Using Eye Characteristic Matching
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Solution Overview
Problem
Existing augmented reality display technologies struggle to accurately control video presentation based on individual eye characteristics and movements, leading to suboptimal performance and user experience.
Innovation Solution
A display apparatus and method that includes a light source, processor, monitoring section, matching section, and irradiator, which acquire and match eye characteristics and movements to precisely project video display light onto the retina, using a fundus camera, OCT, or light detection apparatus for data acquisition, and a see-through member to compensate for wavelength dispersion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing augmented reality display technologies are used, then video can be displayed on the retina, but the control accuracy of video presentation based on individual eye characteristics is insufficient
Solution Approach 1:
The system performs preliminary actions by acquiring and storing the distribution of eyeball characteristics (such as fovea position, blind spot location, and retinal curvature) before video display. This pre-acquired data is used to create a customized coordinate system for each user, enabling accurate video presentation without requiring complex real-time measurements during display operation.
Solution Approach 2:
The invention changes the parameter approach by transitioning from generic display coordinates to personalized eyeball characteristic-based coordinates. By using parameters such as individual fovea position, blind spot location, and retinal curvature radius, the system achieves precise control of video presentation tailored to each user's unique eye structure.
2Productivity
If pattern matching methods are used for eye tracking, then eye movement can be detected, but the processing intensity is excessively high
Solution Approach 1:
The invention replaces complex mechanical pattern matching algorithms with a simplified coordinate transformation system. Instead of performing intensive pixel-by-pixel pattern recognition, the system uses pre-defined coordinate relationships based on eyeball characteristics to directly calculate video presentation positions, dramatically reducing processing intensity and time.
Solution Approach 2:
The coordinate system and transformation relationships are established in advance based on acquired eyeball characteristics. This preliminary setup eliminates the need for complex real-time pattern matching during video display, allowing the system to quickly determine video positions through simple coordinate transformations rather than intensive image processing.
3Manufacturing precision
If a coordinate system based on eyeball characteristics is defined, then video presentation accuracy is improved, but the device complexity increases
Solution Approach 1:
The system introduces a personalized coordinate system defined by key eyeball characteristic parameters such as fovea position, blind spot location, and retinal curvature radius. These parameters serve as reference points that simplify the coordinate transformation process while maintaining high video presentation accuracy, avoiding the need for complex three-dimensional modeling.
Solution Approach 2:
Instead of requiring complete and complex three-dimensional mapping of the entire eyeball structure, the invention focuses on key local characteristics such as the fovea and blind spot positions. By optimizing video presentation accuracy around these critical local points, the system achieves high overall accuracy without the computational burden of complete eyeball modeling.
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 video presentation control and accuracy by defining a coordinate system based on eye characteristics, allowing for precise stimulation of specific retinal points, improving user experience and reducing processing intensity compared to pattern matching methods.
Implementation Method 1
an acquisition section that acquires the distribution of the characteristics of the eyeball. In this case, the acquisition section may include at least one selected from the group consisting of a fundus camera, an OCT, a refractometer, and a light detection apparatus that detects light that returns due to IR scanning.
Implementation Method 2
the monitoring section may monitor the state of the eyeball using a corneal reflex or a fundus reflex.
Implementation Method 3
a see-through member to compensate for wavelength dispersion
Data Source
AI summary
To provide a display apparatus that makes it possible to further improve a performance in controlling video presentation according to characteristics of an eyeball of a user. A display apparatus is provided that includes a light source; a processor that performs processing on a distribution of characteristics of an eyeball; a monitoring section that monitors a state of the eyeball; a matching section that performs matching on the distribution of the characteristics of the eyeball and the state of the eyeball; and an irradiator that irradiates a specified position on a retina with video display light emitted by the light source.