Exploring human visual system: study to aid the development of automatic facial expression recognition framework

Rizwan Ahmed Khan 1 Alexandre Meyer 1 Hubert Konik 2 Saïda Bouakaz 1
1 SAARA - Simulation, Analyse et Animation pour la Réalité Augmentée
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
2 LHC - Laboratoire Hubert Curien [Saint Etienne]
Abstract : This paper focus on understanding human visual system when it decodes or recognizes facial expressions. Results presented can be exploited by the computer vision research community for the development of robust descriptor based on human visual system for facial expressions recognition. We have conducted psycho-visual experimental study to find which facial region is perceptually more attractive or salient for a particular expression. Eye movements of 15 observers were recorded with an eye-tracker in free viewing conditions as they watch a collection of 54 videos selected from Cohn-Kanade facial expression database, showing six universal facial expressions. The results of the study shows that for some facial expressions only one facial region is perceptually more attractive than others. Other cases shows the attractiveness of two to three facial regions. This paper also proposes a novel framework for automatic recognition of expressions which is based on psycho-visual study.
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Communication dans un congrès
Conference on Computer Vision and Pattern Recognition(CVPR), Workshop on Gesture Recognition, Jun 2012, Rhode Island, United States. pp.49-54, 2012
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https://hal-ujm.archives-ouvertes.fr/ujm-00714091
Contributeur : Hubert Konik <>
Soumis le : mardi 3 juillet 2012 - 14:53:50
Dernière modification le : jeudi 19 avril 2018 - 14:38:06
Document(s) archivé(s) le : jeudi 15 décembre 2016 - 20:00:11

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  • HAL Id : ujm-00714091, version 1

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Rizwan Ahmed Khan, Alexandre Meyer, Hubert Konik, Saïda Bouakaz. Exploring human visual system: study to aid the development of automatic facial expression recognition framework. Conference on Computer Vision and Pattern Recognition(CVPR), Workshop on Gesture Recognition, Jun 2012, Rhode Island, United States. pp.49-54, 2012. 〈ujm-00714091〉

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