Opportunistic Traffic Sensing Using Existing Video Sources (Phase II) [2017]

Details

• Creators:
  Eriksson, Jakob ; Jin, Yanzi ; Gerlich, Tomas
• Corporate Creators:
  Illinois Center for Transportation ; University of Illinois at Chicago. Dept. of Computer Science
• Corporate Contributors:
  Illinois. Department of Transportation. Bureau of Materials and Physical Research ; United States. Federal Highway Administration
• Subject/TRT Terms:
  • Traffic surveillance
  • Video cameras
  • Remote sensing
  • Tracking systems
  • Computer vision
  • Red light running
  • Traffic law enforcement
  • computer vision
  • vehicle tracking
  • optical flow
• Publication/ Report Number:
  FHWA-ICT-17-002
• Resource Type:
  Tech Report
• Geographical Coverage:
  Illinois
• Corporate Publisher:
  Illinois Center for Transportation
• Abstract:
  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. Our 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. Our 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.
• Format:
  PDF
• Funding:
  R27-169
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/32025/dot_32025_DS1.pdf
• File Type:
  [PDF - 994.57 KB]
• Collection(s):
  US Transportation Collection
• Main Document Checksum:
  urn:sha256:30c94c718da5ae403fadddc1ea5019ce16d0dbf20de53f58ac942af29a9e48f0