Video player controlled by gesture based on convolutional neural network

Yuxin Zhong; Qujiang Lei; Yunfu Deng; Jingzhou Yang; Zhihao Li; Gen Yang

doi:10.1117/12.2559708

31 January 2020 Video player controlled by gesture based on convolutional neural network

Yuxin Zhong, Qujiang Lei, Yunfu Deng, Jingzhou Yang, Zhihao Li, Gen Yang

Proceedings Volume 11433, Twelfth International Conference on Machine Vision (ICMV 2019); 114331Y (2020) https://doi.org/10.1117/12.2559708
Event: Twelfth International Conference on Machine Vision, 2019, Amsterdam, Netherlands

Abstract

In this paper, we propose an economical system for remote video player control. Through this system, we can use several simple gestures to control the video player, and these gestures can be alternated based on the user’s requirement and habits. The datasets used to train the gesture recognition model are recorded by a simple web camera in the laboratory. We utilize the CNN (convolutional neural network) to train the datasets and the user interface is designed by PyQt5. The gesture recognition system can be applied to switching television programs, controlling video games and household appliances etc.

Citation Download Citation

Yuxin Zhong, Qujiang Lei, Yunfu Deng, Jingzhou Yang, Zhihao Li, and Gen Yang "Video player controlled by gesture based on convolutional neural network", Proc. SPIE 11433, Twelfth International Conference on Machine Vision (ICMV 2019), 114331Y (31 January 2020); https://doi.org/10.1117/12.2559708

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