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A Model Based Method for Automatic Facial Expression Recognition

  • Hans van Kuilenburg
  • Marco Wiering
  • Marten den Uyl
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3720)

Abstract

Automatic facial expression recognition is a research topic with interesting applications in the field of human-computer interaction, psychology and product marketing. The classification accuracy for an automatic system which uses static images as input is however largely limited by the image quality, lighting conditions and the orientation of the depicted face. These problems can be partially overcome by using a holistic model based approach called the Active Appearance Model. A system will be described that can classify expressions from one of the emotional categories joy, anger, sadness, surprise, fear and disgust with remarkable accuracy. It is also able to detect smaller, local facial features based on minimal muscular movements described by the Facial Action Coding System (FACS). Finally, we show how the system can be used for expression analysis and synthesis.

Keywords

Facial Expression Face Image Emotional Expression Hide Neuron Input Neuron 
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 2005

Authors and Affiliations

  • Hans van Kuilenburg
    • 1
  • Marco Wiering
    • 2
  • Marten den Uyl
    • 1
  1. 1.VicarVisionAmsterdamThe Netherlands
  2. 2.Utrecht UniversityUtrechtThe Netherlands

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