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Objects Detection and Tracking in Highly Congested Traffic Using Compressed Video Sequences

  • Marcin Bernaś
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7594)

Abstract

The paper presents a model to detect and track vehicles in highly congested traffic using low quality (usually compressed) video sequences. Robustness of the model is provided by applying a data fusion for various detection and tracking algorithms. The surveys to find reliable detection algorithms were performed. Basing on the experiments, the model calibration and results were presented. The proposed model provides data, which can be used by traffic engineers in various microscopic traffic simulations.

Keywords

Video Sequence Background Subtraction Object Detection Object Tracking Vehicle Detection 
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 2012

Authors and Affiliations

  • Marcin Bernaś
    • 1
  1. 1.Faculty of TransportSilesian University of TechnologyKatowicePoland

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