Title :

Consistent Optical Flow Maps for full and micro facial expression recognition

Author(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]

Conference title :

VISAPP

City :

Porto

Country :

Portugal

Start date of the conference :

2017-02-27

Journal title :

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

Publisher :

SCITEPRESS - Science and Technology Publications

Publication date :

2017-02-27

English keyword(s) :

Facial expression
Micro-expression
Optical Flow

HAL domain(s) :

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

English abstract : [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 ...
Show more >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.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

Comment :

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