AI-Assisted Object Detection for Individuals with Visual Impairments
DOI:
https://doi.org/10.58445/rars.3998Keywords:
Accessibility, Affordability, AI-Assistance, Computer VisionAbstract
Visual impairment impacts over 250 million people worldwide, causing day-to-day difficulties for these individuals. While traditional tools like white canes and guide dogs are essential for mobility, they cannot verbally identify specific objects or obstacles in the user's environment. This project introduces a proof of concept for an AI-assisted object detection system designed to bridge that gap. We utilized Google's Teachable Machine and TensorFlow.js to create a browser-based model that identifies objects and announces them via a text-to-speech engine. We tested the system using various optical setups, including webcams and smartphones, and image data was processed locally on hardware ranging from high-performance laptops to standard Chromebooks. Our results showed that the model achieved extremely high accuracy for specific object classes while maintaining real-time performance on low-cost devices. This study demonstrates that accessible, browser-based computer vision technologies can effectively enhance safety and independence for the visually impaired without requiring expensive, specialized hardware.
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