• Skip to primary navigation
  • Skip to main content
Logo

Work Zone Safety Information Clearinghouse

Library of Resources to Improve Roadway Work Zone Safety for All Roadway Users

  • About
  • Join Listserv
  • Contact
  • Twitter
  • Facebook
  • LinkedIn
  • Work Zone Data
    • At a Glance
    • National & State Traffic Data
    • Work Zone Traffic Crash Trends and Statistics
    • Worker Fatalities and Injuries at Road Construction Sites
  • Topics of Interest
    • Commercial Motor Vehicle Safety
    • Smart Work Zones
    • Transportation Management Plans
    • Accommodating Pedestrians
    • Worker Safety and Welfare
    • Project Coordination in Work Zones
  • Training
    • Flagger
    • Online Courses
    • Toolboxes
    • FHWA Safety Grant Products
    • Certification and
      Accreditation
  • Work Zone Devices
  • Laws, Standards & Policies
    • COVID-19 Guidance
  • Public Awareness
  • Events
  • About
  • Listserv
  • Contact
  • Search
Publication

Single Camera Worker Detection, Tracking and Action Recognition in Construction Site

Author/Presenter: Ishioka, Hiroaki; Weng, Xinshuo; Man, Yunze; Kitani, Kris
Abstract:

In Japan, the construction industry strongly be needed productivity improvement and increasing the number of new hires due to improvement of working environment. Site manager needs to grasp whether the daily progress is as planned and updates the schedule appropriately for improve site’s productivity and safety. In image-based data acquisition approach in Japan, there is a problem that learning is insufficient with only global public data, since construction worker in Japan has originality in image feature compare with other countries. In this study, we make original dataset for additional learning firstly. Then we proposed domain-specific algorithms specific to the Japan construction site, including a worker detection and tracking algorithm and a worker action recognition algorithm. As a result, our worker detection showed 87.9% accuracy in same-site evaluation and 77.5% accuracy in cross-site evaluation. Our worker action recognition showed 60.2% mean accuracy. Finally, the method of translation into activity element based on the output value of worker detection was indicated.

Source: 37th International Symposium on Automation and Robotics in Construction
Publication Date: 2020
Full Text URL: Link to URL
Publication Types: Books, Reports, Papers, and Research Articles
Topics: Video Imaging Detectors; Work Zones; Worker Safety

Copyright © 2023 American Road & Transportation Builders Association (ARTBA). The National Work Zone Safety Information Clearinghouse is a project of the ARTBA Transportation Development Foundation. It is operated in cooperation with the U.S. Federal Highway Administration and Texas A&M Transportation Institute. | Copyright Statement · Privacy Policy · Disclaimer
American Road and Transportation Builders Association Transportation Development Foundation, American Road and Transportation Builders Association U.S. Department of Transportation Federal Highway Administration Texas A&M Transportation Institute