Multiple Local Curvature Gabor Binary Patterns for Facial Action Recognition
Détails
Etat: Public
Version: de l'auteur⸱e
ID Serval
serval:BIB_617B1CD800CB
Type
Actes de conférence (partie): contribution originale à la littérature scientifique, publiée à l'occasion de conférences scientifiques, dans un ouvrage de compte-rendu (proceedings), ou dans l'édition spéciale d'un journal reconnu (conference proceedings).
Collection
Publications
Institution
Titre
Multiple Local Curvature Gabor Binary Patterns for Facial Action Recognition
Titre de la conférence
HBU 2013, International Workshop on Human Behavior Understanding, in conjunction with ACM Multimedia
Statut éditorial
Publié
Date de publication
2013
Volume
8212
Série
Lecture Notes in Computer Science
Pages
136-147
Langue
anglais
Résumé
Curvature Gabor features have recently been shown to be
powerful facial texture descriptors with applications on
face recognition. In this paper we introduce their use in
facial action unit (AU) detection within a novel
framework that combines multiple Local Curvature Gabor
Binary Patterns (LCGBP) on different filter sizes and
curvature degrees. The proposed system uses the distances
of LCGBP histograms between neutral faces and AU
containing faces combined with an AU-specific feature
selection and classification process. We achieve 98.6%
overall accuracy in our tests with the extended
Cohn-Kanade database, which is higher than achieved
previously by any state-of-the-artmethod.
powerful facial texture descriptors with applications on
face recognition. In this paper we introduce their use in
facial action unit (AU) detection within a novel
framework that combines multiple Local Curvature Gabor
Binary Patterns (LCGBP) on different filter sizes and
curvature degrees. The proposed system uses the distances
of LCGBP histograms between neutral faces and AU
containing faces combined with an AU-specific feature
selection and classification process. We achieve 98.6%
overall accuracy in our tests with the extended
Cohn-Kanade database, which is higher than achieved
previously by any state-of-the-artmethod.
Mots-clé
Facial action unit detection, Curvature Gabor Wavelets, Local Binary Patterns, Automatic facial expression, analysis
Création de la notice
06/01/2014 21:46
Dernière modification de la notice
20/08/2019 15:18
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