Opportunistic Traffic Sensing Using Existing Video Sources (Phase II)

The purpose of the project reported on here was to investigate methods for automatic traffic sensing using traffic surveillance cameras, red light cameras, and other permanent and pre-existing video sources. Success in this direction would potentially yield the ability to produce continuous, daily traffic counts where such video sources exist, as compared to the occasional traffic studies performed today. The methods investigated come from the field of computer vision, including optical flow, background subtraction, and object detection and tracking, as well as control theory for the fusing of the results of these methods. The system outperforms the state of the art in vehicle tracking, and it runs at faster frame rate. More work remains in improving robustness to occlusion and to improve accuracy of nighttime imagery. The authors' work on rigid motion optical flow was published in the proceedings of the International Conference on 3D Vision, and our work on vehicle tracking is currently under submission to the IEEE Winter Conference on Applications of Computer Vision.

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    University of Illinois, Chicago

    Department of Computer Science, 851 South Morgan Street
    Chicago, IL  United States  60607-7053

    Illinois Department of Transportation

    Bureau of Materials and Physical Research
    126 East Ash Street
    Springfield, IL  United States  62704-4766

    Federal Highway Administration

    1200 New Jersey Avenue, SE
    Washington, DC  United States  20590
  • Authors:
    • Eriksson, Jakob
    • Jin, Yanzi
    • Gerlich, Tomas
  • Publication Date: 2017-2


  • English

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Filing Info

  • Accession Number: 01630120
  • Record Type: Publication
  • Report/Paper Numbers: FHWA-ICT-17-002, ICT-17-003, UILU-ENG-2017-2003
  • Contract Numbers: R27-169
  • Created Date: Mar 27 2017 9:30AM