Stereoscopic Vision Defect Simulation via Selective Image Distortion
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Solution Overview
Problem
Current simulations of vision defects lack accuracy and individualization, as they rely heavily on patient testimonials and static, 2D representations, failing to effectively convey the complex visual distortions experienced by individuals with vision impairments.
Innovation Solution
A processor-implemented method and electronic device that receive and process stereoscopic images, applying selective distortions to simulate vision defects by merging distorted and undistorted images, providing a more immersive and contextually relevant simulation experience using head-mounted displays.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If simulations rely on patient testimonials and generalized understandings, then the simulation can be created more easily, but the accuracy and individualization of the simulation deteriorates
Solution Approach 1:
The system creates accurate copies of individual patients' actual visual experiences by processing their eye examination data and visual defect measurements. Instead of relying on generalized models, the simulation copies the specific visual distortions, acuity levels, and field defects measured from each patient's actual eye condition, thereby achieving high accuracy without sacrificing ease of creation.
Solution Approach 2:
The system transforms raw eye examination parameters (visual acuity measurements, field defect coordinates, refraction data) into simulated visual experience parameters. By changing and adapting these parameters from clinical measurements to simulation-specific parameters, the system achieves both individualization and ease of implementation through standardized data transformation processes.
2Device complexity
If static 2D representations are used to simulate vision defects, then the implementation is simpler, but the immersive experience and contextual relevance deteriorates
Solution Approach 1:
The system transitions from static 2D representations to dynamic stereoscopic 3D visual simulations. By adding the depth dimension through stereoscopic imaging and enabling real-time interaction, the simulation provides an immersive experience that mirrors actual visual defect conditions while maintaining manageable implementation complexity through established VR/AR technologies.
Solution Approach 2:
The system transforms static visual defect representations into dynamic, interactive simulations that respond to user actions and environmental context. The simulation adapts in real-time based on user movement, gaze direction, and interaction with virtual objects, providing contextual relevance that static images cannot achieve while using dynamic rendering techniques that are computationally efficient.
3Adaptability or versatility
If generalized simulations are used, then they can represent common vision defects, but they fail to represent individualized visual reactions to real-life situations
Solution Approach 1:
The system applies local quality by customizing the simulation to each patient's specific visual defect pattern. Instead of using a single generalized model, the simulation locally adapts distortion fields, acuity zones, and field defects to match the individual patient's measured conditions, preserving unique visual experience characteristics while still representing common defect types.
Solution Approach 2:
The system segments the visual field into multiple zones with different defect characteristics based on the patient's specific condition. By dividing the visual experience into distinct regions (central vision, peripheral vision, blind spots, distorted zones), the simulation can represent complex individualized patterns while maintaining overall coverage of common vision defect types through standardized segmentation approaches.
Data Source
AI summary
A method for providing a simulation of a vision defect is disclosed. The method includes: receiving a first image of a scene and a second image of the scene, the first image corresponding to a first viewpoint of the scene and the second image corresponding to a second viewpoint of the scene; applying one or more first distortions to only a selected one of the first and second images; generating a stereoscopic image by merging the distorted one of the first and second images and an undistorted one of the first and second images; and displaying the stereoscopic image on a display.