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Tracking of Individuals in Very Long Video Sequences

  • P. Fihl
  • R. Corlin
  • S. Park
  • T. B. Moeslund
  • M. M. Trivedi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4291)

Abstract

In this paper we present an approach for automatically detecting and tracking humans in very long video sequences. The detection is based on background subtraction using a multi-mode Codeword method. We enhance this method both in terms of representation and in terms of automatically updating the background allowing for handling gradual and rapid changes. Tracking is conducted by building appearance-based models and matching these over time. Tests show promising detection and tracking results in a ten hour video sequence.

Keywords

Video Sequence Gaussian Mixture Model Background Subtraction Body Model Appearance 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 2006

Authors and Affiliations

  • P. Fihl
    • 1
  • R. Corlin
    • 1
  • S. Park
    • 2
  • T. B. Moeslund
    • 1
  • M. M. Trivedi
    • 2
  1. 1.Laboratory of Computer Vision and Media TechnologyAalborg UniversityDenmark
  2. 2.Computer Vision and Robotics Research LaboratoryThe University of CaliforniaSan DiegoUSA

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