Print Page
Sign Language Recognition Using Accurate ASL Gesture Detection System
Author: Florida Atlantic University
Published: 2024/12/16
Publication Type: Simulation, Modelling – Peer-Reviewed: Yes
Topic: AI and Disabilities (Publications Database)
Page Content: Synopsis Introduction Main Item
Synopsis: Study pioneers an accurate system for recognizing American Sign Language gestures using advanced computer vision and deep learning, significantly enhancing communication accessibility.
Why it matters: This article on sign language recognition details a groundbreaking approach to recognizing American Sign Language (ASL) gestures using advanced computer vision and deep learning techniques. By combining MediaPipe for hand movement tracking with the YOLOv8 model, the researchers achieved a highly accurate system (with accuracy rates of up to 98%) for detecting and classifying ASL alphabet gestures. This innovation has significant implications for breaking down communication barriers between the deaf and hard-of-hearing community and the hearing world, enabling more inclusive interactions in various settings such as education, healthcare, and social environments. The study’s findings and methodologies offer a promising direction for future advancements in assistive technology, contributing to a more inclusive society by enhancing communication accessibility – Disabled World.
Introduction
Sign language serves as a sophisticated means of communication vital to individuals who are deaf or hard-of-hearing, relying on hand movements, facial expressions, [...]