Context Data to Improve Association in Visual Tracking Systems

  • A. M. Sánchez
  • M. A. Patricio
  • J. García
  • J. M. Molina
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4528)


A key aspect in visual surveillance systems is robust movement segmentation, which is still a difficult and unresolved problem. In this paper, we propose an architecture based on a two-layer image-processing modules: General Tracking Layer (GTL) and Context Layer (CL). GTL describe a generic multipurpose tracking process for video-surveillance systems. CL is designed as a symbolic reasoning system that manages the symbolic interface data between GTL modules in order to asses a specific situation and take the appropriate decision about visual data association. Our architecture has been used to improve the association process of a tracking system and tested in two different scenarios to show the advantages in improved performance and output continuity.


Tracking System Near Neighbor Data Association Context Data Mobile Object 
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Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • A. M. Sánchez
    • 1
  • M. A. Patricio
    • 1
  • J. García
    • 1
  • J. M. Molina
    • 1
  1. 1.Universidad Carlos III de Madrid, Computer Science Department, Applied Artificial Intelligence Group, Avda. Universidad Carlos III 22, 28270 Colmenarejo (Madrid) 

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