Titre :

Consistent Optical Flow Maps for full and micro facial expression recognition

Auteur(s) :

Allaert, Benjamin [Auteur]
Université de Lille, Sciences et Technologies
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Bilasco, Ioan Marius [Auteur]
Université de Lille, Sciences et Technologies
FOX MIIRE [LIFL]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Djeraba, Chaabane [Auteur]
FOX MIIRE [LIFL]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Institut de Recherche sur les Composants logiciels et matériels pour l'Information et la Communication Avancée - UAR 3380 [IRCICA]

Titre de la manifestation scientifique :

VISAPP

Ville :

Porto

Pays :

Portugal

Date de début de la manifestation scientifique :

2017-02-27

Titre de la revue :

Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications

Éditeur :

SCITEPRESS - Science and Technology Publications

Date de publication :

2017-02-27

Mot(s)-clé(s) en anglais :

Facial expression
Micro-expression
Optical Flow

Discipline(s) HAL :

Informatique [cs]/Vision par ordinateur et reconnaissance de formes [cs.CV]

Résumé en anglais : [en]

A wide variety of face models have been used in the recognition of full or micro facial expressions in image sequences. However, the existing methods only address one family of expression at a time, as micro-expressions ...
Lire la suite >A wide variety of face models have been used in the recognition of full or micro facial expressions in image sequences. However, the existing methods only address one family of expression at a time, as micro-expressions are quite different from full-expressions in terms of facial movement amplitude and/or texture changes. In this paper we address the detection of micro and full-expression with a common facial model characterizing facial movements by means of consistent Optical Flow estimation. Optical Flow extracted from the face is generally noisy and without specific processing it can hardly cope with expression recognition requirements especially for micro-expressions. Direction and magnitude statistical profiles are jointly analyzed in order to filter out noise and obtain and feed consistent Optical Flows in a face motion model framework. Experiments on CK+ and CASME2 facial expression databases for full and micro expression recognition show the benefits brought by the proposed approach in the filed of facial expression recognition.Lire moins >

Langue :

Anglais

Comité de lecture :

Oui

Audience :

Internationale

Vulgarisation :

Non

Commentaire :

Consistent Optical Flow Maps for full and micro facial expression recognition. Available from: https://www.researchgate.net/publication/311517985_Consistent_Optical_Flow_Maps_for_full_and_micro_facial_expression_recognition [accessed Apr 7, 2017]

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL