Facial Expression Modelling from Still Images Using a Single Generic 3D Head Model

  • Michael Hähnel
  • Andreas Wiratanaya
  • Karl-Friedrich Kraiss
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4174)


We propose two approaches to facial expression modelling from single still images using a generic 3D head model without the need of large image databases (like e.g. Active Appearance Models). The first approach estimates the parameters of linear muscle models to obtain a biologically inspired model of the facial expression which may be changed intuitively afterwards. The second approach uses RBF-based interpolation to deform the head model according to the given expression. As a preprocessing stage for face recognition, this approach could achieve significantly higher recognition rates than in the un-normalized case based on the Eigenface approach, local binary patterns and a grey-scale correlation measure.


Facial Expression Feature Point Face Recognition Face Image Local Binary Pattern 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Michael Hähnel
    • 1
  • Andreas Wiratanaya
    • 1
  • Karl-Friedrich Kraiss
    • 1
  1. 1.Institute of Man-Machine-InteractionRWTH Aachen UniversityGermany

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