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Person-Flow Estimation with Preserving Privacy Using Multiple 3D People Counters

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Science and Technologies for Smart Cities (SmartCity360° 2020)

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Abstract

The spread of mobile phones made it easy to estimate person-flow for corporate marketing, crowd analysis, and countermeasures for disaster and disease. However, due to recent privacy concerns, regulations have been tightened around the world and most smartphone operating systems have increased privacy protection. To solve this, in this study, we propose the person-flow estimation technique with preserving privacy. We use 3D People Counter which can record only the time and direction of passing people, a person’s height, and walking speed, therefore it preserves privacy from the moment of collecting data. To estimate people’s in-out data, we propose four methods and they use some of the sensor data above in different combinations. We compared these methods and the height-based method could estimate about 79% of the sensor data as in-out data. Additionally, we also created a system to interpolate in-out data into person-flow data and to visualize it. By using this method, we believe that it can be used for the purposes described in the beginning.

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Acknowledgement

This research is supported by the Commissioned Research of National Institute of Information and Communications Technology (NICT) and MIC SCOPE (No. 191506001).

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Authors and Affiliations

  1. Nagoya University, Nagoya, Aichi, Japan

    Yoshiteru Nagata, Takuro Yonezawa & Nobuo Kawaguchi

Authors
  1. Yoshiteru Nagata
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  2. Takuro Yonezawa
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  3. Nobuo Kawaguchi
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Corresponding author

Correspondence to Yoshiteru Nagata .

Editor information

Editors and Affiliations

  1. School of Technology and Management, Escola Superior de Tecnologia e Gestão, VIANA DO CASTELO, Portugal

    Sara Paiva

  2. Polytechnic Institute of Viana do Castel, Viana do Castelo, Portugal

    Sérgio Ivan Lopes

  3. SIC Laboratory, INSEEC U, ECE Paris Graduate School of Engineering, PARIS, France

    Rafik Zitouni

  4. Vaagdevi College of Engineering, Telangana, India

    Nishu Gupta

  5. University of Minho, Guimarães, Portugal

    Sérgio F. Lopes

  6. Nagoya University, Nagoya, Japan

    Takuro Yonezawa

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Nagata, Y., Yonezawa, T., Kawaguchi, N. (2021). Person-Flow Estimation with Preserving Privacy Using Multiple 3D People Counters. In: Paiva, S., Lopes, S.I., Zitouni, R., Gupta, N., Lopes, S.F., Yonezawa, T. (eds) Science and Technologies for Smart Cities. SmartCity360° 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 372. Springer, Cham. https://doi.org/10.1007/978-3-030-76063-2_41

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  • DOI: https://doi.org/10.1007/978-3-030-76063-2_41

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-76062-5

  • Online ISBN: 978-3-030-76063-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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