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Pattern Analysis and Applications

, Volume 18, Issue 1, pp 135–143 | Cite as

Optical flow-based observation models for particle filter tracking

  • Manuel LucenaEmail author
  • Jose Manuel Fuertes
  • Nicolas Perez de la Blanca
Short Paper

Abstract

This paper presents three observation models suitable for particle filter tracking, based on the optical flow of the sequence. Modern optical flow computation techniques can obtain in real time very accurate estimates, so we can use it as a source of evidence for higher level image processing. Our image motion-based models are based, respectively, on: a previously computed optical flow field, the image brightness constraint, and similarity measures. They take into account not only the consistency of the measured optical flow with the motion predicted by the model, but also the presence of optical flow discontinuities on the object boundary. Experimental results show that the resulting trackers are comparable to other, state-of-the-art tracking methods. While the model based on similarity measures provides better performance, the optical flow-field-based model is a suitable option when the flow field is available.

Keywords

Object Tracking Optical Flow Particle Filter 

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Copyright information

© Springer-Verlag London 2014

Authors and Affiliations

  • Manuel Lucena
    • 1
    Email author
  • Jose Manuel Fuertes
    • 1
  • Nicolas Perez de la Blanca
    • 2
  1. 1.Department of Computer Science, Escuela Politecnica SuperiorUniversity of JaenJaénSpain
  2. 2.Department of Computer Science and A.IUniversity of GranadaGranadaSpain

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