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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Paschero, M. Del Vescovo, G. Benucci, L. Rizzi, A. Santello, M. Fabbri, G. Mascioli, F.M.F. |
| Copyright Year | 2012 |
| Description | Author affiliation: Università di Roma ‘Sapienza’, Information Eng., Electronics and Telecom. Dpt. - Polo per la Mobilità Sostenibile, Via Eudossiana 18, 00184, Italy (Paschero, M.; Del Vescovo, G.; Benucci, L.; Rizzi, A.; Fabbri, G.; Mascioli, F.M.F.) || School of Biological and Health Systems Engineering, Arizona State University Tempe, 85287-9709, USA (Santello, M.) |
| 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. |
| Starting Page | 1690 |
| Ending Page | 1695 |
| File Size | 745348 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781467301596 |
| ISSN | 21635145 |
| e-ISBN | 9781467301589 |
| e-ISBN | 9781467301572 |
| DOI | 10.1109/ISIE.2012.6237345 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-05-28 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Face Training Emotion recognition Mouth Real time systems Face detection Streaming media |
| Content Type | Text |
| Resource Type | Article |
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