Visual Surveillance for Moving Vehicles

  • Authors:
  • James M. Ferryman;Stephen J. Maybank;Anthony D. Worrall

  • Affiliations:
  • Computational Vision Group, Department of Computer Science, The University of Reading, Berkshire RG6 6AY, England, UK. j.m.ferryman@reading.ac.uk;Computational Vision Group, Department of Computer Science, The University of Reading, Berkshire RG6 6AY, England, UK;Computational Vision Group, Department of Computer Science, The University of Reading, Berkshire RG6 6AY, England, UK

  • Venue:
  • International Journal of Computer Vision - Special issue on a special section on visual surveillance
  • Year:
  • 2000

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Abstract

An overview is given of a vision system for locating, recognising and tracking multiple vehicles, using an image sequence taken by a single camera mounted on a moving vehicle. The camera motion is estimated by matching features on the ground plane from one image to the next. Vehicle detection and hypothesis generation are performed using template correlation and a 3D wire frame model of the vehicle is fitted to the image. Once detected and identified, vehicles are tracked using dynamic filtering. A separate batch mode filter obtains the 3D trajectories of nearby vehicles over an extended time. Results are shown for a motorway image sequence.