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Model-based object tracking in traffic scenes

  • D. Koller
  • K. Daniilidis
  • T. Thórhallson
  • H. -H. Nagel
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 588)

Abstract

This contribution addresses the problem of detection and tracking of moving vehicles in image sequences from traffic scenes recorded by a stationary camera. In order to exploit the a priori knowledge about the shape and the physical motion of vehicles in traffic scenes, a parameterized vehicle model is used for an intraframe matching process and a recursive estimator based on a motion model is used for motion estimation. The initial guess about the position and orientation for the models are computed with the help of a clustering approach of moving image features. Shadow edges of the models are taken into account in the matching process. This enables tracking of vehicles under complex illumination conditions and within a small effective field of view. Results on real world traffic scenes are presented and open problems are outlined.

Keywords

Line Segment Motion Model Extend Kalman Filter Matching Process Vehicle Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1992

Authors and Affiliations

  • D. Koller
    • 1
  • K. Daniilidis
    • 1
  • T. Thórhallson
    • 1
  • H. -H. Nagel
    • 1
    • 2
  1. 1.Institut für Algorithmen und Kognitive Systeme Fakultät für InformatikUniversität Karlsruhe (TH)Karlsruhe 1Germany
  2. 2.Fraunhofer-Institut für Informations- und Datenverarbeitung (IITB)Karlsruhe

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