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Conference Papers Year : 2010

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

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.
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Dates and versions

hal-00829354 , version 1 (03-06-2013)

Identifiers

  • HAL Id : hal-00829354 , version 1

Cite

Stefano Berretti, Alberto del Bimbo, Pietro Pala, Boulbaba Ben Amor, Daoudi Mohamed. A Set of Selected SIFT Features for 3D Facial Expression Recognition. 20th International Conference on Pattern Recognition, Aug 2010, Istanbul, Turkey. pp.4125 - 4128. ⟨hal-00829354⟩
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