Video-Based Vehicle Detection and Tracking Using Spatiotemporal Maps

Surveillance video cameras have been increasingly deployed along roadways over the past decade. Automatic traffic data collection through surveillance video cameras is highly desirable; however, sight-degrading factors and camera vibrations make it an extremely challenging task. In this paper, a computer-vision–based algorithm for vehicle detection and tracking is presented, implemented, and tested. This new algorithm consists of four steps: user initialization, spatiotemporal map generation, strand analysis, and vehicle tracking. It relies on a single, environment-insensitive cue that can be easily obtained and analyzed without camera calibration. The proposed algorithm was implemented in Microsoft Visual C++ using OpenCV and Boost C++ graph libraries. Six test video data sets, representing a variety of lighting, flow level, and camera vibration conditions, were used to evaluate the performance of the new algorithm. Experimental results showed that environmental factors do not significantly impact the detection accuracy of the algorithm. Vehicle count errors ranged from 8% to 19% in the tests, with an overall average detection accuracy of 86.6%. Considering that the test scenarios were chosen to be challenging, such test results are encouraging.

• Record URL:
  https://doi.org/10.3141/2121-09
• Summary URL:
  http://scholar.google.com/scholar_lookup?title=Video-Based+Vehicle+Detection+and+Tracking+Using+Spatiotemporal+Maps&author=Y.+Malinovskiy&author=Y.+Wu&author=Y.+Wang&publication_year=2009
• Availability:
  • Find a library where document is available. Order URL: http://trb.org/Main/Blurbs/Data_Systems_and_Travel_Survey_Methods_2009_162816.asp
• Authors:
  • Malinovskiy, Yegor
  • Wu, Yao-Jan
  • Wang, Yinhai
  • 0000-0002-4180-5628
• Publication Date: 2009

Language

• English

Media Info

• Media Type: Print
• Features: Figures; References; Tables;
• Pagination: pp 81-89
• Monograph Title: Data Systems and Travel Survey Methods 2009
• Serial:
  • Transportation Research Record: Journal of the Transportation Research Board
  • Issue Number: 2121
  • Publisher: Transportation Research Board
  • ISSN: 0361-1981

Subject/Index Terms

• TRT Terms: Accuracy; Algorithms; Automatic data collection systems; Computer vision; Traffic data; Traffic surveillance; Vibration; Video cameras
• Uncontrolled Terms: Spatiotemporal traffic contour maps; Vehicle detection and tracking; Vehicle tracking
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; I73: Traffic Control;

Filing Info

• Accession Number: 01128605
• Record Type: Publication
• ISBN: 9780309126380
• Report/Paper Numbers: 09-1580
• Files: TRIS, TRB, ATRI
• Created Date: May 19 2009 7:48AM