Using Adaptive Tracking to Classify and Monitor Activities in a Site

  • Authors:
  • W. E. L. Grimson;C. Stauffer;R. Romano;L. Lee

  • Affiliations:
  • -;-;-;-

  • Venue:
  • CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
  • Year:
  • 1998

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Abstract

We describe a vision system that monitors activity in a site over extended periods of time. The system uses a distributed set of sensors to cover the site, and an adaptive tracker detects multiple moving objects in the sensors. Our hypothesis is that motion tracking is sufficient to support a range of computations about site activities. We demonstrate using the tracked motion data: to calibrate the distributed sensors, to construct rough site models, to classify detected objects, to learn common patterns of activity for different object classes, and to detect unusual activities.