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| Paper Title: | Sign Language Translation Using 3D Sensor |
| Authors Name: | Sakshi Borgude , Aditya Kanawade , Sandesh Shardul , Sneha Sonawane |
| Unique Id: | IJSDR2305172 |
| Published In: | Volume 8 Issue 5, May-2023 |
| Abstract: | Deaf people around the world don’t have any other means of communication rather than sign language among themselves as well as normal peoples. They mainly rely on hand gestures and signs in shapes made with hands. Sign language is the way through which deaf and dumb people can communicate with each other. It has been observed that, impaired people find it very difficult to interact with the society. Normal individuals can't able to understand their sign language. To bridge this gap, the proposed system acts as the mediator between impaired and normal people. This System uses Kinect camera to capture the signs. The Kinect camera captures 3D dynamic gesture. Thus the method is proposed for feature extraction of dynamic gesture of Indian Sign Language(ISL). As American Sign Language (ASL) is popularly used in the field of research and development, ISL on the other hand has been standardized recently and hence its ISL recognition is less explored. The propose method extracts feature from the sign and Converts it to the intended textual form. The method then integrates local as well as global information of the signs. This integrated feature improves the performance of the system, the system serves as an aid to disabled people. Its application includes hospitals, government sectors and some multinational companies. Concepts like machine learning and feature extraction will be used. |
| Keywords: | Indian Sign language, American Sign Language, Kinect camera, Machine learning, Feature Extraction. |
| Cite Article: | "Sign Language Translation Using 3D Sensor", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.8, Issue 5, page no.1086 - 1093, May-2023, Available :http://www.ijsdr.org/papers/IJSDR2305172.pdf |
| Downloads: | 000223172 |
| Publication Details: | Published Paper ID: IJSDR2305172 Registration ID:206444 Published In: Volume 8 Issue 5, May-2023 DOI (Digital Object Identifier): Page No: 1086 - 1093 Publisher: IJSDR | www.ijsdr.org ISSN Number: 2455-2631 |
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