Arabic Sign Language Recognition System Using 2D Hands and Body Skeleton Data

Arabic Sign Language Recognition System Using 2D Hands and Body Skeleton Data

This paper presents a novel Arabic Sign Language (ArSL) recognition system, using selected 2D hands and body key points from successive video frames. The system recognizes the recorded video signs, for both signer dependent and signer independent modes, using the concatenation of a 3D CNN skeleton n...

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Bibliographic Details
Main Authors: Mohamed A. Bencherif, Mohammed Algabri, Mohamed A. Mekhtiche, Mohammed Faisal, Mansour Alsulaiman, Hassan Mathkour, Muneer Al-Hammadi, Hamid Ghaleb
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Arabic sign language
OpenPose
skeleton
key points
parallel convolutions
Online Access:https://ieeexplore.ieee.org/document/9389720/

Internet

https://ieeexplore.ieee.org/document/9389720/

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