A Set of Selected SIFT Features for 3D Facial Expression Recognition

  • Authors:
  • Stefano Berretti;Alberto Del Bimbo;Pietro Pala;Boulbaba Ben Amor;Mohamed Daoudi

  • Affiliations:
  • -;-;-;-;-

  • Venue:
  • ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
  • Year:
  • 2010

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Abstract

In this paper, the problem of person-independent facial expression recognition is addressed on 3D shapes. To this end, an original approach is proposed that computes SIFT descriptors on a set of facial landmarks of depth images, and then selects the subset of most relevant features. Using SVM classification of the selected features, an average recognition rate of 77.5% on the BU-3DFE database has been obtained. Comparative evaluation on a common experimental setup, shows that our solution is able to obtain state of the art results.