Emotion Recognition by Body Movement ...
Type de document :
Autre communication scientifique (congrès sans actes - poster - séminaire...): Communication dans un congrès avec actes
Titre :
Emotion Recognition by Body Movement Representation on the Manifold of Symmetric Positive Definite Matrices
Auteur(s) :
Daoudi, Mohamed [Auteur]
Modeling and Analysis of Static and Dynamic Shapes [3D-SAM]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Ecole nationale supérieure Mines-Télécom Lille Douai [IMT Nord Europe]
Berretti, Stefano [Auteur]
Dipartimento di Sistemi e Informatica [DSI]
Pala, Pietro [Auteur]
Dipartimento di Sistemi e Informatica [DSI]
Delevoye, Yvonne [Auteur]
Laboratoire Sciences Cognitives et Sciences Affectives - UMR 9193 [SCALab]
Bimbo, Alberto [Auteur]
Dipartimento di Sistemi e Informatica [DSI]
Modeling and Analysis of Static and Dynamic Shapes [3D-SAM]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Ecole nationale supérieure Mines-Télécom Lille Douai [IMT Nord Europe]
Berretti, Stefano [Auteur]
Dipartimento di Sistemi e Informatica [DSI]
Pala, Pietro [Auteur]
Dipartimento di Sistemi e Informatica [DSI]
Delevoye, Yvonne [Auteur]
Laboratoire Sciences Cognitives et Sciences Affectives - UMR 9193 [SCALab]
Bimbo, Alberto [Auteur]
Dipartimento di Sistemi e Informatica [DSI]
Titre de la manifestation scientifique :
International Conference on Image Analysis and Processing, ICIAP 2017
Ville :
Catania
Pays :
Italie
Date de début de la manifestation scientifique :
2017-09-11
Date de publication :
2017-09-11
Discipline(s) HAL :
Informatique [cs]/Vision par ordinateur et reconnaissance de formes [cs.CV]
Sciences cognitives/Psychologie
Sciences cognitives/Neurosciences
Sciences cognitives/Psychologie
Sciences cognitives/Neurosciences
Résumé en anglais : [en]
Emotion recognition is attracting great interest for its potential application in a multitude of real-life situations. Much of the Computer Vision research in this field has focused on relating emotions to facial expressions, ...
Lire la suite >Emotion recognition is attracting great interest for its potential application in a multitude of real-life situations. Much of the Computer Vision research in this field has focused on relating emotions to facial expressions, with investigations rarely including more than upper body. In this work, we propose a new scenario, for which emotional states are related to 3D dynamics of the whole body motion. To address the complexity of human body movement, we used covariance descrip-tors of the sequence of the 3D skeleton joints, and represented them in the non-linear Riemannian manifold of Symmetric Positive Definite matrices. In doing so, we exploited geodesic distances and geometric means on the manifold to perform emotion classification. Using sequences of spontaneous walking under the five primary emotional states, we report a method that succeeded in classifying the different emotions, with comparable performance to those observed in a human-based force-choice classification task.Lire moins >
Lire la suite >Emotion recognition is attracting great interest for its potential application in a multitude of real-life situations. Much of the Computer Vision research in this field has focused on relating emotions to facial expressions, with investigations rarely including more than upper body. In this work, we propose a new scenario, for which emotional states are related to 3D dynamics of the whole body motion. To address the complexity of human body movement, we used covariance descrip-tors of the sequence of the 3D skeleton joints, and represented them in the non-linear Riemannian manifold of Symmetric Positive Definite matrices. In doing so, we exploited geodesic distances and geometric means on the manifold to perform emotion classification. Using sequences of spontaneous walking under the five primary emotional states, we report a method that succeeded in classifying the different emotions, with comparable performance to those observed in a human-based force-choice classification task.Lire moins >
Langue :
Anglais
Comité de lecture :
Oui
Audience :
Internationale
Vulgarisation :
Non
Projet ANR :
Collections :
Source :
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- https://hal.archives-ouvertes.fr/hal-01546654/document
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- http://arxiv.org/pdf/1707.07180
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- https://hal.archives-ouvertes.fr/hal-01546654/document
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- https://hal.archives-ouvertes.fr/hal-01546654/file/iciap-2017-9%20%281%29.pdf
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- https://hal.archives-ouvertes.fr/hal-01546654/document
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- document
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- iciap-2017-9%20%281%29.pdf
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- 1707.07180
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