Improved Local Binary Pattern Based Action Unit Detection Using Morphological and Bilateral Filters

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ID Serval
serval:BIB_8B93103209B8
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
Titre
Improved Local Binary Pattern Based Action Unit Detection Using Morphological and Bilateral Filters
Titre de la conférence
FG 2013, 10th IEEE International Conference on Automatic Face and Gesture Recognition
Auteur(s)
Yuce A., Sorci M., Thiran J.P.
Adresse
Shanghai, China, April 22-26, 2013
Statut éditorial
Publié
Date de publication
2013
Langue
anglais
Résumé
Automatic facial action unit (AU) detection in videos is
the key ingredient to all systems that utilize a subject
face for either interaction or analysis purposes. With
the ever growing range of possible applications,
achieving a high accuracy in the simplest possible manner
gains even more importance. In this paper, we present new
features obtained by applying local binary patterns to
images processed by morphological and bilateral filters.
We use as features the variations of these patterns
between the expressive and neutral faces, and show that
we can gain a considerable amount of accuracy increase by
simply applying these fundamental image processing tools
and choosing the right way of representing the patterns.
We also use these features in conjunction with additional
features based on facial point geometrical relations
between frames and achieve detection rates higher than
methods previously proposed, using a small number of
features and basic support vector machine classification.
Mots-clé
LTS5, Facial Expression Recognition, Action Unit, Detection, Local Binary Patterns, Morphology by, Reconstruction, Bilateral Filters
Création de la notice
06/01/2014 21:46
Dernière modification de la notice
03/03/2018 19:12
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