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WiCLR: A Sign Language Recognition System Framework Based on Wireless Sensing

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Broadband Communications, Networks, and Systems (Broadnets 2019)

Abstract

The non-intrusion and device-free sign language recognition (SLR) is of great significance to improve the quality of life, broaden living space and enhance social service for the deaf and mute. In this paper, we propose a SLR system framework, called WiCLR, for identifying isolated words in Chinese sign language exploring the channel state information (CSI). WiCLR is made up entirely of commercial wireless devices, which does not incur significant deployment and maintenance overhead. In the framework we devise a signal denoising method to remove the environment noise and the internal state transitions in commercial devices. Moreover, we propose the multi-stream anomaly detection algorithm in action segmentation and fusion. Finally, the extreme learning machine (ELM) is utilized to meet the accuracy and real-time requirements. The experiment results show that the recognition accuracy of the approach reaches 94.3% and 91.7% respectively in an empty conference room and a laboratory.

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Authors and Affiliations

  1. School of Information Science and Engineering, Yanshan University, Qinhuangdao, 066004, China

    Wang Lin, Liu Yu & Jing Nan

  2. Army Military Transportation University, Tianjin, 300171, China

    Liu Yu

  3. Key Lab of Software Engineering in Hebei Province, Qinhuangdao, 066004, Hebei, China

    Wang Lin, Liu Yu & Jing Nan

Authors
  1. Wang Lin
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  2. Liu Yu
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  3. Jing Nan
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Corresponding author

Correspondence to Wang Lin .

Editor information

Editors and Affiliations

  1. Xidian University, Xi'an, China

    Qingshan Li

  2. Xidian University, Xi'an, China

    Shengli Song

  3. Xidian University, Xi'an, China

    Rui Li

  4. Xidian University, Xi'an, China

    Yueshen Xu

  5. Xi’an Jiaotong University, Xi'an, Shaanxi, China

    Wei Xi

  6. Shanghai University, Shanghai, China

    Honghao Gao

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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Lin, W., Yu, L., Nan, J. (2019). WiCLR: A Sign Language Recognition System Framework Based on Wireless Sensing. In: Li, Q., Song, S., Li, R., Xu, Y., Xi, W., Gao, H. (eds) Broadband Communications, Networks, and Systems. Broadnets 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 303. Springer, Cham. https://doi.org/10.1007/978-3-030-36442-7_7

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  • DOI: https://doi.org/10.1007/978-3-030-36442-7_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-36441-0

  • Online ISBN: 978-3-030-36442-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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