Using Optical Flow for Tracking

  • M. Lucena
  • J. M. Fuertes
  • N. Perez de la Blanca
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2905)


We present two observation models based on optical flow information to track objects using particle filter algorithms. Although, in principle, the optical flow information enables us to know the displacement of the objects present in a scene, it cannot be used directly to displace a model since flow estimation techniques lack the necessary precision. We will define instead two observation models for using into probabilistic tracking algorithms: the first uses an optical flow estimation computed previously, and the second is based directly on correlation techniques over two consecutive frames.


Computer Vision Optical Flow Consecutive Frame Observation Model Uniform Background 
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 2003

Authors and Affiliations

  • M. Lucena
    • 1
  • J. M. Fuertes
    • 1
  • N. Perez de la Blanca
    • 2
  1. 1.Departamento de Informatica, Escuela Politecnica SuperiorUniversidad de JaenJaenSpain
  2. 2.Departamento de Ciencias de la Computacion e Inteligencia ArtificialETSII. Universidad de GranadaGranadaSpain

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