Personal Identification Methods Using Footsteps of One Step

Yuki Hori, Takahiro Ando, Akira Fukuda

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In recent years, it has been shown that it is possible to identify individuals by walking footsteps, and research is being conducted to improve the recognition rate. The conventional method targets multiple footsteps and imposes many restrictions on the recording conditions. The task has further required precise, manual segmentation of the sequence of footsteps for analysis of the observation waveform. On the other hand, in our previous research, we have proposed a method that can robustly identify only the footstep of one step, with few restrictions for recording conditions and extraction methods. In this paper, we investigate whether our proposed method can identify individuals only by the difference in walking sound for each person regardless of the presence and difference of shoes. As a result, we found that the proposal method using SVM or CNN can identify with average accuracy 98 % and distinguish between subjects without being affected by shoes.

Original languageEnglish
Title of host publication2020 International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages73-78
Number of pages6
ISBN (Electronic)9781728149851
DOIs
Publication statusPublished - Feb 2020
Event2nd International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020 - Fukuoka, Japan
Duration: Feb 19 2020Feb 21 2020

Publication series

Name2020 International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020

Conference

Conference2nd International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020
CountryJapan
CityFukuoka
Period2/19/202/21/20

All Science Journal Classification (ASJC) codes

  • Information Systems and Management
  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Information Systems
  • Signal Processing

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  • Cite this

    Hori, Y., Ando, T., & Fukuda, A. (2020). Personal Identification Methods Using Footsteps of One Step. In 2020 International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020 (pp. 73-78). [9065230] (2020 International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICAIIC48513.2020.9065230