A Real-time Computer Vision System for Measuring Traffic Parameters

  • Authors:
  • Philip McLauchlan;David Beymer;Benn Coifman;Jitendra Mali

  • Affiliations:
  • -;-;-;-

  • Venue:
  • CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
  • Year:
  • 1997

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Abstract

For the problem of tracking vehicles on freeways using machine vision, existing systems work well in free-flowing traffic. Traffic engineers, however, are more interested in monitoring freeways when there is congestion, and current systems break down for congested traffic due to the problem of partial occlusion. We have developed a feature-based tracking approach for the task of tracking vehicles under congestion. Instead of tracking entire vehicles, vehicle sub-features are tracked to make the system robust to partial occlusion. In order to group together sub-features that come from the same vehicle, the constraint of common motion is used. Here we describe the real-time implementation of the system using a network of DSP chips.