Advertisement

Deep Learning Based Gesture Recognition System for Immersive Broadcasting Production

  • Meeree Park
  • Sung Geun Yoo
  • Minjeong Song
  • Sangil ParkEmail author
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 536)

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.

Keywords

Gesture recognition Deep learning Immersive broadcasting MEMS sensor Internet of things 

Notes

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).

References

  1. 1.
    Choi, J., Lee, H., Lee, S.: Deep learning-based hand gesture recognition algorithm using multi-modality information. In: 2017 Summer Conference, pp. 672–673. The Institute of Electronics and Information Engineers (2017)Google Scholar
  2. 2.
    Sood, S.K., Mahajan, I.: Wearable IoT sensor based healthcare system for identifying and controlling chikungunya virus. Comput. Ind. 91, 33–44 (2017)CrossRefGoogle Scholar
  3. 3.
    Hiremath, S., Yang, G., & Mankodiya, K.: Wearable Internet of Things: concept, architectural components and promises for person-centered healthcare. In: 2014 EAI 4th International Conference on Wireless Mobile Communication and Healthcare (Mobihealth), pp. 304–307. IEEE, November 2014Google Scholar
  4. 4.
    Varatharajan, R., Manogaran, G., Priyan, M.K., Sundarasekar, R.: Wearable sensor devices for early detection of Alzheimer disease using dynamic time warping algorithm. Cluster Comput. 1–10 (2017)Google Scholar
  5. 5.
    Castillejo, P., Martinez, J.F., Rodriguez-Molina, J., Cuerva, A.: Integration of wearable devices in a wireless sensor network for an E-health application. IEEE Wirel. Commun. 20(4), 38–49 (2013)CrossRefGoogle Scholar
  6. 6.
    NG, K.K.R., Rajeshwari, K.: Interactive clothes based on IOT using NFC and Mobile Application. In: 2017 IEEE 7th Annual Computing and Communication Workshop and Conference (CCWC), pp. 1–4. IEEE, January 2017Google Scholar
  7. 7.
    Perera, C., Jayaraman, P., Zaslavsky, A., Christen, P., Georgakopoulos, D.: Dynamic configuration of sensors using mobile sensor hub in internet of things paradigm. In: 2013 IEEE Eighth International Conference on Intelligent Sensors, Sensor Networks and Information Processing, pp. 473–478. IEEE, April 2013Google Scholar
  8. 8.
    Zhou, W., Piramuthu, S.: Security/privacy of wearable fitness tracking IoT devices. In: 2014 9th Iberian Conference on Information Systems and Technologies (CISTI), pp. 1–5. IEEE, June 2014Google Scholar
  9. 9.
    Rautaray, S.S., Agrawal, A.: Vision based hand gesture recognition for human computer interaction: a survey. Artif. Intell. Rev. 43(1), 1–54 (2015)CrossRefGoogle Scholar
  10. 10.
    Garg, P., Aggarwal, N., Sofat, S.: Vision based hand gesture recognition. World Acad. Sci. Eng. Technol. 49(1), 972–977 (2009)Google Scholar
  11. 11.
    Lee, S.: Application of logistic regression model and its validation for landslide susceptibility mapping using GIS and remote sensing data. Int. J. Remote Sens. 26(7), 1477–1491 (2005)CrossRefGoogle Scholar
  12. 12.
    Fleury, A., Vacher, M., Noury, N.: SVM-based multimodal classification of activities of daily living in health smart homes: sensors, algorithms, and first experimental results. IEEE Trans. Inf Technol. Biomed. 14(2), 274–283 (2010)CrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Meeree Park
    • 1
  • Sung Geun Yoo
    • 1
  • Minjeong Song
    • 1
  • Sangil Park
    • 1
    Email author
  1. 1.Nano IT Design Fusion Graduate SchoolSeoultechSeoulRepublic of Korea

Personalised recommendations