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Vision

Vision

Vision is the result of light being detected and transduced into neural signals by the retina of the eye. This information is then further analyzed and interpreted by the brain. First, light enters the front of the eye and is focused by the cornea and lens onto the retina—a thin sheet of neural tissue lining the back of the eye. Because of refraction through the convex lens of the eye, images are projected onto the retina upside-down and reversed.

Visual System

Visual System

Light enters the eye through the cornea, a transparent, dome-shaped surface covering the surface of the eyeball that helps to direct and focus incoming light. This light is then channeled toward the pupil, an adjustable opening whose size is controlled by the iris. The iris, a pigmented muscle, regulates the amount of light entering the eye by contracting or dilating the pupil, thereby ensuring optimal light levels for clear vision.
Once through the pupil, the light passes through the lens, a...

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Embedded AI system for interactive vision screen based on human action recognition.

Duan Chi¹, Wang Zhi¹, Hao Luo²

¹Zhe Jiang Key Laboratory of General Aviation Operation Technology, Jiande, China.

The Review of Scientific Instruments

|June 1, 2022

Summary

This summary is machine-generated.

This study introduces an intelligent self-service vision screening system using AI and pose estimation. It enables individuals to perform vision tests independently, improving efficiency for large-scale screenings.

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Area of Science:

Computer Vision
Human-Computer Interaction
Ophthalmology

Background:

Myopia significantly impacts school-aged children globally.
Traditional vision screening methods are laborious and time-consuming.
There is a need for efficient, scalable vision screening solutions.

Purpose of the Study:

To propose an intelligent, self-service vision screening system.
To enable independent vision testing without technical staff assistance.
To leverage AI for efficient and rapid vision screening.

Main Methods:

Human action recognition using pose estimation (real-time joint localization, detection, association, tracking).
Development of a system on a compact, embedded AI platform.
Integration of a red-green-blue-Depth (RGB-D) sensor for ranging and pose extraction.
Design of intuitive upper-limb actions for recognition and interaction.

Main Results:

The system allows individuals to perform vision screening independently.
Demonstrated efficiency and convenience for large-scale vision screening.
Experimental results validated the effectiveness of the proposed technique.

Conclusions:

The intelligent self-service vision screening system offers a convenient solution.
AI-powered pose estimation enhances the efficiency of vision tests.
This technology facilitates rapid and large-scale vision screening initiatives.