Presentation
Towards Emotion Recognition: A Persistent Entropy Application
Author/s | González Díaz, Rocío
Paluzo Hidalgo, Eduardo Quesada Moreno, José Francisco |
Department | Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial Universidad de Sevilla. Departamento de Matemática Aplicada I (ETSII) |
Publication Date | 2019 |
Deposit Date | 2019-06-11 |
Published in |
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ISBN/ISSN | 978-3-030-10827-4 0302-9743 |
Abstract | Emotion recognition and classification is a very active area of research. In this paper, we present
a first approach to emotion classification using persistent entropy and support vector machines. A
topology-based model ... Emotion recognition and classification is a very active area of research. In this paper, we present a first approach to emotion classification using persistent entropy and support vector machines. A topology-based model is applied to obtain a single real number from each raw signal. These data are used as input of a support vector machine to classify signals into 8 different emotions (calm, happy, sad, angry, fearful, disgust and surprised). |
Citation | González Díaz, R., Paluzo Hidalgo, E. y Quesada Moreno, J.F. (2019). Towards Emotion Recognition: A Persistent Entropy Application. En CTIC 2019 : 7th International Workshop on Computational Topology in Image Contex (96-109), Málaga, España: Springer. |
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Towards Emotion Recognition.pdf | 2.150Mb | [PDF] | View/ | |