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...
| Autores: | , |
|---|---|
| Tipo de recurso: | artículo |
| Fecha de publicación: | 2015 |
| País: | España |
| Institución: | Universitat Autònoma de Barcelona |
| Repositorio: | Dipòsit Digital de Documents de la UAB |
| Idioma: | inglés |
| OAI Identifier: | oai:ddd.uab.cat:144806 |
| Acceso en línea: | https://ddd.uab.cat/record/144806 https://dx.doi.org/urn:doi:10.5565/rev/elcvia.795 |
| Access Level: | acceso abierto |
| Palabra clave: | Emotion recognition Affective computing Artificial intelligence Human computer interaction |
| Sumario: | 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. |
|---|