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Optimised Particle Filter Approaches to Object Tracking in Video Sequences

  • Artur Loza
  • Fanglin Wang
  • Miguel A. Patricio
  • Jesús García
  • José M. Molina
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5601)

Abstract

In this paper, the ways of optimising a Particle Filter video tracking algorithm are investigated. The optimisation scheme discussed in this work is based on hybridising a Particle Filter tracker with a deterministic mode search technique applied to the particle distribution. Within this scheme, an extension of the recently introduced structural similarity tracker is proposed and compared with the approach based on separate and combined colour and mean-shift tracker. The new approach is especially applicable to real-world video surveillance scenarios, in which the presence of multiple targets and complex background pose a non-trivial challenge to automated trackers. The preliminary results indicate that a considerable improvement in tracking is achieved by applying the optimisation scheme, at the price of a moderate computational complexity increase of the algorithm.

Keywords

Video Sequence Particle Filter Proposal Distribution Video Tracking Importance Density 
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 2009

Authors and Affiliations

  • Artur Loza
    • 1
  • Fanglin Wang
    • 2
  • Miguel A. Patricio
    • 3
  • Jesús García
    • 3
  • José M. Molina
    • 3
  1. 1.University of BristolUnited Kingdom
  2. 2.Shanghai Jiao Tong UniversityChina
  3. 3.Universidad Carlos III de MadridSpain

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