Comparing Feature Point Tracking with Dense Flow Tracking for Facial Expression Recognition

  • José V. Ruiz
  • Belén Moreno
  • Juan José Pantrigo
  • Ángel Sánchez
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5602)


This work describes a research which compares the facial expression recognition results of two point-based tracking approaches along the sequence of frames describing a facial expression: feature point tracking and holistic face dense flow tracking. Experiments were carried out using the Cohn-Kanade database for the six types of prototypic facial expressions under two different spatial resolutions of the frames (the original one and the images reduced to a 40% of its original size). Our experimental results showed that the dense flow tracking method provided in average for the considered types of expressions a better recognition rate (95.45% of success) than feature point flow tracking (91.41%) for the whole test set of facial expression sequences.


Facial Expression Feature Point Facial Expression Recognition Facial Point Facial Action Code System 
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

  • José V. Ruiz
    • 1
  • Belén Moreno
    • 1
  • Juan José Pantrigo
    • 1
  • Ángel Sánchez
    • 1
  1. 1.Departamento de Ciencias de la ComputaciónUniversidad Rey Juan CarlosMadridSpain

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