Initial Evaluation of Vehicle Type Identification using Roadside Stereo Microphones

Billy Dawton, Shigemi Ishida, Yuki Hori, Masato Uchino, Yutaka Arakawa, Shigeaki Tagashira, Akira Fukuda

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

6 Citations (Scopus)

Abstract

A key feature of Intelligent Transport Systems (ITS) is the ability to detect and identify vehicles. In this paper, we put forward a stereo microphone-based system capable of detecting and identifying the type of individually, sequentially, and simultaneously passing vehicles in multi-lane environments based on their sound. We find that our proposed system shows improved performance over single-microphone systems thanks to its improved sequential and successive vehicle detection performance. Initial evaluation results using sound data collected from roads on a university campus show a classification accuracy of 95.01 %.

Original languageEnglish
Title of host publication2020 IEEE Sensors Applications Symposium, SAS 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728148427
DOIs
Publication statusPublished - Mar 2020
Event15th IEEE Sensors Applications Symposium, SAS 2020 - Kuala Lumpur, Malaysia
Duration: Mar 9 2020Mar 11 2020

Publication series

Name2020 IEEE Sensors Applications Symposium, SAS 2020 - Proceedings

Conference

Conference15th IEEE Sensors Applications Symposium, SAS 2020
Country/TerritoryMalaysia
CityKuala Lumpur
Period3/9/203/11/20

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Instrumentation

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