What is it about?
Indian Sign Language (ISL) is practiced by those who speak through hand gestures, but it's not comprehensible to everyone. This project provides a tool that captures hand gestures in real time and displays them as text. With a simple webcam and software, the system brings communication into common life for everyone by making gesture-based messages accessible to a larger extent and with ease.
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Photo by Samantha Gades on Unsplash
Why is it important?
This paper introduces a low-cost, live system to translate Indian Sign Language gestures to text from simply a webcam and general software tools. As opposed to earlier methods that used custom hardware or deep neural networks, our system uses light-weight classification techniques, which are more deployable and accessible. This is a useful step towards inclusive communication within schools, workplaces, and public services — especially timely as digital accessibility becomes a greater concern around the world.
Perspectives
Preparing this publication has been one of the most rewarding experiences of my academic career. It stemmed from a need to produce something useful and accessible — a device that could actually assist those who use gesture communication. It was very fulfilling to experience how cheap technology and basic machine learning methods could be transformed to bridge gaps in communication. I hope that this work will motivate others to pursue solutions that make ordinary life more connected and inclusive.
UDAY GUNTURU
Sathyabama University
Read the Original
This page is a summary of: Indian sign language detection using Sklearn classification techniques, January 2025, American Institute of Physics,
DOI: 10.1063/5.0264908.
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