Design concept of sign language recognition translation and gesture recognition control system based on deep learning and machine vision

Yiyang Zhang; Xin Pu; Xiaolu Wang; Haopeng Guo; Ke Liu; QianQing Yang; Lili Wang

doi:10.1117/12.2653702

18 November 2022 Design concept of sign language recognition translation and gesture recognition control system based on deep learning and machine vision

Yiyang Zhang, Xin Pu, Xiaolu Wang, Haopeng Guo, Ke Liu, QianQing Yang, Lili Wang

Author Affiliations +

Proceedings Volume 12473, Second International Conference on Optics and Communication Technology (ICOCT 2022); 124731X (2022) https://doi.org/10.1117/12.2653702
Event: Second International Conference on Optics and Communication Technology (ICOCT 2022), 2022, Hefei, China

Abstract

With the development of society, gestures are used in many aspects, but the computer's functionality for gesture recognition is still to be improved. This article is mainly a preliminary idea of a basic gesture recognition system built based on the existing Google deep learning framework TensorFlow and gesture recognition components in MediaPipe and OpenCv machine vision open-source library. The training dataset is first subjected to skeleton key point coordinate extraction, then the pre-processed dataset is used to train the neural network and constitute the preliminary model, and finally the model is corrected and changed in the end.

Citation Download Citation

Yiyang Zhang, Xin Pu, Xiaolu Wang, Haopeng Guo, Ke Liu, QianQing Yang, and Lili Wang "Design concept of sign language recognition translation and gesture recognition control system based on deep learning and machine vision", Proc. SPIE 12473, Second International Conference on Optics and Communication Technology (ICOCT 2022), 124731X (18 November 2022); https://doi.org/10.1117/12.2653702

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