A Survey on Human Emotion Recognition Approaches, Databases and Applications

This paper presents the various emotion classification and recognition systems which implement methods aiming at improving Human Machine Interaction. The modalities and approaches used for affect detection vary and contribute to accuracy and efficacy in detecting emotions of human beings. This paper...

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Detalhes bibliográficos
Autores: Vinola, C., Vimaladevi, K.
Tipo de documento: artigo
Data de publicação:2015
País:España
Recursos:Universitat Autònoma de Barcelona
Repositório:Dipòsit Digital de Documents de la UAB
Idioma:inglês
OAI Identifier:oai:ddd.uab.cat:144806
Acesso em linha:https://ddd.uab.cat/record/144806
https://dx.doi.org/urn:doi:10.5565/rev/elcvia.795
Access Level:Acceso aberto
Palavra-chave:Emotion recognition
Affective computing
Artificial intelligence
Human computer interaction
Descrição
Resumo:This paper presents the various emotion classification and recognition systems which implement methods aiming at improving Human Machine Interaction. The modalities and approaches used for affect detection vary and contribute to accuracy and efficacy in detecting emotions of human beings. This paper discovers them in a comparison and descriptive manner. Various applications that use the methodologies in different contexts to address the challenges in real time are discussed. This survey also describes the databases that can be used as standard data sets in the process of emotion identification. Thus an integrated discussion of methods, databases used and applications pertaining to the emerging field of Affective Computing (AC) is done and surveyed. This paper presents the various emotion classification and recognition systems which implement methods aiming at improving Human Machine Interaction. The modalities and approaches used for affect detection vary and contribute to accuracy and efficacy in detecting emotions of human beings. This paper discovers them in a comparison and descriptive manner. Various applications that use the methodologies in different contexts to address the challenges in real time are discussed. This survey also describes the databases that can be used as standard data sets in the process of emotion identification. Thus an integrated discussion of methods, databases used and applications pertaining to the emerging field of Affective Computing (AC) is done and surveyed.