Paper
23 May 2023 Sign language recognition using MediaPipe
Yuheng Wang, Renshi Li, Guan Li
Author Affiliations +
Proceedings Volume 12604, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2022); 1260434 (2023) https://doi.org/10.1117/12.2674613
Event: 2nd International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2022), 2022, Guangzhou, China
Abstract
Sign language recognition is a popular and important problem in computer vision. This paper uses MediaPipe as a method of feature extraction to extract coordinates of the joint points of the human body. The sign language dataset used in this paper is 64 Argentine sign languages (LSA64). Then the coordinate data is input to Long-Short Term Memory (LSTM) and Gated Recurrent Unit (GRU) neural networks. After testing two models in 640 videos, the result has shown that the accuracy of the trained LSTM and GRU model reaches 94.0625% and 94.5312%, respectively. It is able to recognize 64 Argentinian sign language words or phrases. As a convenient method of sign language recognition, it is feasible in reality.
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Yuheng Wang, Renshi Li, and Guan Li "Sign language recognition using MediaPipe", Proc. SPIE 12604, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2022), 1260434 (23 May 2023); https://doi.org/10.1117/12.2674613
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KEYWORDS
Neural networks

Feature extraction

Video

3D modeling

Computer vision technology

Deep learning

Visualization

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