Abstract
In this paper, we implement a system that provides the convenience of personal broadcasting production by recognizing the user’s operation using the sensor tag and implementing the function corresponding to the operation. The system can acquire sensor data and learn the data through deep learning to distinguish the user’s gesture. In this paper, we study the process of recognition of data through the data acquisition process and the deep learning process using the sensor tag and propose a method to perform the function using it.
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Acknowledgement
This work was supported by Institute for Information & communications Technology Promotion (IITP) grant funded by the Korea government (MSIT) (No. 2016-0-00099, Personal Broadcast Technology Development for Production Convenience and Maximum Viewing Experience).
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Park, M., Yoo, S.G., Song, M., Park, S. (2020). Deep Learning Based Gesture Recognition System for Immersive Broadcasting Production. In: Park, J., Park, DS., Jeong, YS., Pan, Y. (eds) Advances in Computer Science and Ubiquitous Computing. CUTE CSA 2018 2018. Lecture Notes in Electrical Engineering, vol 536. Springer, Singapore. https://doi.org/10.1007/978-981-13-9341-9_19
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DOI: https://doi.org/10.1007/978-981-13-9341-9_19
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