Recently there is a great interest in artificial systems able to understand and recognize human emotions. In this paper an Emotion Recognition System based on classical neural networks and neuro-fuzzy classifiers is proposed. Emotion recognition is performed in real time starting from a video stream acquired by a common webcam monitoring the user's face. Neurofuzzy classifiers, in comparison with Multi Layer Perceptron trained by EBP algorithm, show very short training times, allowing applications with easy and automated set up procedures, to be used in a wide range of applications, from entertainment to safety. The algorithm yields very interesting performances and can be adopted to recognize emotions as well as possible pathological conditions of the individual to be monitored. © 2012 IEEE.

A real time classifier for emotion and stress recognition in a vehicle driver / Paschero, Maurizio; DEL VESCOVO, Guido; Leonardo, Benucci; Rizzi, Antonello; Marco, Santello; Fabbri, Gianluca; FRATTALE MASCIOLI, Fabio Massimo. - STAMPA. - (2012), pp. 1690-1695. ((Intervento presentato al convegno 21st IEEE International Symposium on Industrial Electronics (ISIE) tenutosi a Hangzhou; China nel MAY 28-31, 2012 [10.1109/isie.2012.6237345].

A real time classifier for emotion and stress recognition in a vehicle driver

PASCHERO, Maurizio;DEL VESCOVO, Guido;RIZZI, Antonello;FABBRI, GIANLUCA;FRATTALE MASCIOLI, Fabio Massimo
2012

Abstract

Recently there is a great interest in artificial systems able to understand and recognize human emotions. In this paper an Emotion Recognition System based on classical neural networks and neuro-fuzzy classifiers is proposed. Emotion recognition is performed in real time starting from a video stream acquired by a common webcam monitoring the user's face. Neurofuzzy classifiers, in comparison with Multi Layer Perceptron trained by EBP algorithm, show very short training times, allowing applications with easy and automated set up procedures, to be used in a wide range of applications, from entertainment to safety. The algorithm yields very interesting performances and can be adopted to recognize emotions as well as possible pathological conditions of the individual to be monitored. © 2012 IEEE.
21st IEEE International Symposium on Industrial Electronics (ISIE)
Classification, Image processing, Neural networks, Neuro-fuzzy classifiers, emotion recognition, real time processing
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
A real time classifier for emotion and stress recognition in a vehicle driver / Paschero, Maurizio; DEL VESCOVO, Guido; Leonardo, Benucci; Rizzi, Antonello; Marco, Santello; Fabbri, Gianluca; FRATTALE MASCIOLI, Fabio Massimo. - STAMPA. - (2012), pp. 1690-1695. ((Intervento presentato al convegno 21st IEEE International Symposium on Industrial Electronics (ISIE) tenutosi a Hangzhou; China nel MAY 28-31, 2012 [10.1109/isie.2012.6237345].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/485914
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