Gesture Recognition to Text Conversion for Human-Computer Interaction Through Computer Vision Technology
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-64779-6_16
Reference19 articles.
1. Chakraborty, B.K., Sarma, D., Bhuyan, M.K., MacDorman, K.F.: Review of constraints on vision-based gesture recognition for human–computer interaction. IET Comput. Vision 12, 3–15 (2017). https://doi.org/10.1049/iet-cvi.2017.0052
2. Fang, W., Ding, Y., Zhang, F., Sheng, J.: Gesture recognition based on CNN and DCGAN for calculation and text output. IEEE Access. 7, 28230–28237 (2019). https://doi.org/10.1109/access.2019.2901930
3. Murtaza, Z., Akmal, H., Afzal, W., Gelani, H.E., Abdin, Z., ul Gulzar, M.H.: Human computer interaction based on gestural cues recognition/sign language to text conversion. In: 2019 International Conference on Engineering and Emerging Technologies (ICEET) (2019). https://doi.org/10.1109/ceet1.2019.8711835
4. Antoshchuk, S., Kovalenko, M., Sieck, J.: Gesture recognition-based human–computer interaction interface for multimedia applications. Digitisation of Culture: Namibian and International Perspectives. 269–286 (2018). https://doi.org/10.1007/978-981-10-7697-8_16
5. Rathour, N., et al.: A Standalone vision device to recognize facial landmarks and smile in real time using raspberry pi and sensor. Int. J. Eng. Adv. Technol. 8, 4383–4388 (2019). https://doi.org/10.35940/ijeat.f8957.088619
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