IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i3p2122-d1044461.html
   My bibliography  Save this article

Use of One-Stage Detector and Feature Detector in Infrared Video on Transport Infrastructure and Tunnels

Author

Listed:
  • David Švorc

    (Faculty of Engineering, Czech University of Life Sciences Prague, 165 00 Prague, Czech Republic)

  • Tomáš Tichý

    (Faculty of Transportation Sciences, Czech Technical University, 110 00 Prague, Czech Republic)

  • Miroslav Růžička

    (Faculty of Engineering, Czech University of Life Sciences Prague, 165 00 Prague, Czech Republic)

  • Petr Ivasienko

    (Faculty of Transportation Sciences, Czech Technical University, 110 00 Prague, Czech Republic)

Abstract

This article presents the use of the combination of the object detection method and feature detector in an infrared video on traffic infrastructure and in tunnels. The theme of the paper is the validation of vehicle detection and its classification using infrared video streams. In addition, the article focuses on the use of a feature detector and object detection to distinguish between vehicles with electric and combustion motors. The method suggests the use of a low-resolution thermal camera as an inexpensive extension of installed thermal camera technologies. The developed system has been verified for the applicability of vehicle detection and classification using object detection methods and their application in transport infrastructure and tunnels. It also presents a method for distinguishing propulsion units into electric and internal combustion; both systems’ conclusions are then statistically verified. The application of the system is evident in regional traffic management systems, including safety applications for traffic control in tunnels. Categorizing vehicles provides valuable information for higher levels of traffic management, toll systems, and municipal database systems, as well as for a preventive system for estimating vehicle conditions and their potential of fire in tunnels.

Suggested Citation

  • David Švorc & Tomáš Tichý & Miroslav Růžička & Petr Ivasienko, 2023. "Use of One-Stage Detector and Feature Detector in Infrared Video on Transport Infrastructure and Tunnels," Sustainability, MDPI, vol. 15(3), pages 1-21, January.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:3:p:2122-:d:1044461
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/3/2122/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/3/2122/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Tomáš Tichý & David Švorc & Miroslav Růžička & Zuzana Bělinová, 2021. "Thermal Feature Detection of Vehicle Categories in the Urban Area," Sustainability, MDPI, vol. 13(12), pages 1-13, June.
    2. Sergiu Cosmin Nistor & Tudor Alexandru Ileni & Adrian Sergiu Dărăbant, 2020. "Automatic Development of Deep Learning Architectures for Image Segmentation," Sustainability, MDPI, vol. 12(22), pages 1-18, November.
    3. Pavol Kuchár & Rastislav Pirník & Tomáš Tichý & Karol Rástočný & Michal Skuba & Tamás Tettamanti, 2021. "Noninvasive Passenger Detection Comparison Using Thermal Imager and IP Cameras," Sustainability, MDPI, vol. 13(22), pages 1-17, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Pavol Kuchár & Rastislav Pirník & Aleš Janota & Branislav Malobický & Jozef Kubík & Dana Šišmišová, 2023. "Passenger Occupancy Estimation in Vehicles: A Review of Current Methods and Research Challenges," Sustainability, MDPI, vol. 15(2), pages 1-27, January.
    2. Pavol Kuchár & Rastislav Pirník & Tomáš Tichý & Karol Rástočný & Michal Skuba & Tamás Tettamanti, 2021. "Noninvasive Passenger Detection Comparison Using Thermal Imager and IP Cameras," Sustainability, MDPI, vol. 13(22), pages 1-17, November.
    3. Tomáš Tichý & David Švorc & Miroslav Růžička & Zuzana Bělinová, 2021. "Thermal Feature Detection of Vehicle Categories in the Urban Area," Sustainability, MDPI, vol. 13(12), pages 1-13, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:3:p:2122-:d:1044461. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.