Facial Expression Recognition Using Diffeomorphic Image Registration Framework

  • Bartlomiej W. Papiez
  • Bogdan J. Matuszewski
  • Lik-Kwan Shark
  • Wei Quan
Conference paper
Part of the Springer Proceedings in Mathematics & Statistics book series (PROMS, volume 30)

Abstract

This paper presents a new method for facial expression modelling and recognition based on diffeomorphic image registration parameterised via stationary velocity fields in the log-Euclidean framework. The validation and comparison are done using different statistical shape models (SSM) built using the Point Distribution Model (PDM), velocity fields and deformation fields. The obtained results show that the facial expression representation based on stationary velocity fields can be successfully utilised in facial expression recognition, and this parameterisation produces a higher recognition rate than the facial expression representation based on deformation fields.

Keywords

Facial expression representation Facial expression recognition Vectorial log-Euclidean statistics Statistical shape modelling Diffeomorphic image registration 

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Bartlomiej W. Papiez
    • 1
  • Bogdan J. Matuszewski
    • 1
  • Lik-Kwan Shark
    • 1
  • Wei Quan
    • 1
  1. 1.Applied Digital Signal and Image Processing Research CentreUniversity of Central LancashirePrestonUK

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