Yağış, Ekin and Ünel, Mustafa (2018) Facial expression based emotion recognition using neural networks. In: Campilho, Aurelio and Karray, Fakhri and Ter Haar Romeny, Bart, (eds.) Image Analysis and Recognition. Lecture Notes in Computer Science, 10882. Springer, Switzerland, pp. 210-217. ISBN 978-3-319-92999-6 (Print) 978-3-319-93000-8 (Online)
![[thumbnail of _469267_1_En_24_Chapter_Author.pdf]](https://research.sabanciuniv.edu/style/images/fileicons/application_pdf.png)
_469267_1_En_24_Chapter_Author.pdf
Download (2MB)
Official URL: http://dx.doi.org/10.1007/978-3-319-93000-8_24
Abstract
Facial emotion recognition has been extensively studied over the last decade due to its various applications in the fields such as human-computer interaction and data analytics. In this paper, we develop a facial emotion recognition approach to classify seven emotional states (joy, sadness, surprise, anger, fear, disgust and neutral). Seventeen action units tracked by Kinect v2 sensor have been used as features. Classification of emotions was performed by artificial neural networks (ANNs). Six subjects took part in the experiment. We have achieved average accuracy of 95.8% for the case in which we tested our approach with the same volunteers took part in our data generation process. We also evaluated the performance of the network with additional volunteers who were not part of the training data and achieved 67.03% classification accuracy.
Item Type: | Book Section / Chapter |
---|---|
Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800-8360 Electronics > TK7885-7895 Computer engineering. Computer hardware T Technology > TJ Mechanical engineering and machinery > TJ163.12 Mechatronics |
Divisions: | Faculty of Engineering and Natural Sciences > Academic programs > Mechatronics Faculty of Engineering and Natural Sciences |
Depositing User: | Mustafa Ünel |
Date Deposited: | 12 Aug 2018 21:12 |
Last Modified: | 12 Aug 2018 21:12 |
URI: | https://research.sabanciuniv.edu/id/eprint/35815 |