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International Conference on Human-Computer Interaction

HCII 2022: Distributed, Ambient and Pervasive Interactions. Smart Living, Learning, Well-being and Health, Art and Creativity pp 69–86Cite as

WiHead: WiFi-Based Head-Pose Estimation

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13326))

Abstract

Due to the impact of Covid-19, people have started to conduct online courses or meetings. However, this makes it difficult to communicate with each other effectively because of the lack of non-verbal communication. Although webcams are available for online courses, etc., people often do not want to turn them on for privacy reasons. Thus, there is a need to develop privacy preserving way to enable non-verbal communication in online learning and work environments. WiFi as a sensor can be used to detect non-verbal gestures such as head poses, and has been increasingly valued due to its advantages of avoiding the effects of light, non-line of sight monitoring, privacy protection, etc. In this paper, we proposed an approach, which uses WiFi CSI data to estimate head pose. Our approach not only use the amplitude and phase data of raw CSI data, but also use the information in frequency domain. Our experiment with proposed approach confirmed the feasibility of head pose estimation based on WiFi CSI data. This has important implications for device-free sensing detection. Especially in today’s world where web conferences and online courses are widely used, WiFi-based head recognition can give feedback to the other party while protecting privacy, which helps to improve the quality and comfort of communication.

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Acknowledgement

This work was supported by JSPS KAKENHI Grant Numbers 20H00622 and 17KT0154.

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Authors and Affiliations

  1. Graduate School of Information Science and Electrical Engineering, Kyushu University, 744, Motooka, Nishi-ku, Fukuoka, 819-0395, Japan

    Yiming Liu

  2. Faculty of Arts and Science, Kyushu University, 744, Motooka, Nishi-ku, Fukuoka, 819-0395, Japan

    Shin’ichi Konomi

Authors
  1. Yiming Liu
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  2. Shin’ichi Konomi
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Corresponding author

Correspondence to Yiming Liu .

Editor information

Editors and Affiliations

  1. Smart Future Initiative, Frankfurt am Main, Germany

    Norbert A. Streitz

  2. Kyushu University, Fukuoka, Japan

    Shin'ichi Konomi

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Liu, Y., Konomi, S. (2022). WiHead: WiFi-Based Head-Pose Estimation. In: Streitz, N.A., Konomi, S. (eds) Distributed, Ambient and Pervasive Interactions. Smart Living, Learning, Well-being and Health, Art and Creativity. HCII 2022. Lecture Notes in Computer Science, vol 13326. Springer, Cham. https://doi.org/10.1007/978-3-031-05431-0_5

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  • DOI: https://doi.org/10.1007/978-3-031-05431-0_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-05430-3

  • Online ISBN: 978-3-031-05431-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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