BAREM: A multimodal dataset of individuals ...
Document type :
Autre communication scientifique (congrès sans actes - poster - séminaire...): Communication dans un congrès avec actes
Title :
BAREM: A multimodal dataset of individuals interacting with an e-service platform
Author(s) :
Belmonte, Romain [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Aissaoui, Amel [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Mihoubi, Sofiane [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Allaert, Benjamin [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Mennesson, Jose [Auteur]
Ecole nationale supérieure Mines-Télécom Lille Douai [IMT Lille Douai]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Bilasco, Ioan Marius [Auteur]
FOX MIIRE [LIFL]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Goncalves, Laurent [Auteur]
SOFTEAM
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Aissaoui, Amel [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Mihoubi, Sofiane [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Allaert, Benjamin [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Mennesson, Jose [Auteur]
Ecole nationale supérieure Mines-Télécom Lille Douai [IMT Lille Douai]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Bilasco, Ioan Marius [Auteur]

FOX MIIRE [LIFL]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Goncalves, Laurent [Auteur]
SOFTEAM
Conference title :
CBMI 2021 - Content-based Multimedia Indexing
City :
Lille / Virtual
Country :
France
Start date of the conference :
2021-06-28
English keyword(s) :
E-service platform
multimodal dataset
behaviour analysis
anomaly detection
multimodal dataset
behaviour analysis
anomaly detection
HAL domain(s) :
Informatique [cs]/Vision par ordinateur et reconnaissance de formes [cs.CV]
English abstract : [en]
The use of e-service platforms has become essential for many applications (administrative documents, online shopping, reservations). Although these platforms have improved significantly the user experience, unexpected and ...
Show more >The use of e-service platforms has become essential for many applications (administrative documents, online shopping, reservations). Although these platforms have improved significantly the user experience, unexpected and stressful situations can occur. Navigation problems (latency, missing information, poor ergonomics) are not always reported to the designers. To address this problem, we propose a multimodal dataset (video, audio, and physiological data) to help implicitly quantify the impact of navigation problems on users when using an e-service platform. A scenario has been designed to generate various navigation problems which can lead to changes in user behaviour. A baseline is proposed to spot changes in user behaviour, opening the way towards automatically qualifying user experiences while using e-service platforms.Show less >
Show more >The use of e-service platforms has become essential for many applications (administrative documents, online shopping, reservations). Although these platforms have improved significantly the user experience, unexpected and stressful situations can occur. Navigation problems (latency, missing information, poor ergonomics) are not always reported to the designers. To address this problem, we propose a multimodal dataset (video, audio, and physiological data) to help implicitly quantify the impact of navigation problems on users when using an e-service platform. A scenario has been designed to generate various navigation problems which can lead to changes in user behaviour. A baseline is proposed to spot changes in user behaviour, opening the way towards automatically qualifying user experiences while using e-service platforms.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
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