Emotion classification using hidden layer outputs

Author

Günler, Mine Altinay ; Tora, Hakan

Author_Institution

EBIS, Data Commun. Dept., Vakiflar Bankasi T.A.O., Ankara, Turkey

fYear

2012

fDate

2-4 July 2012

Firstpage

1

Lastpage

4

Abstract

Neural network (NN) with Multi-Layer Perceptron (MLP) is a supervised learning algorithm composed of artificial neurons. Multilayer NN is capable of solving nonlinear classification problems such as emotion identification by using facial expressions that is presented in this paper. Hidden layer outputs of NN provide useful information about facial appearance. This study addresses that without fully training NN hidden layer outputs can be used as feature. It is shown that an acceptable recognition rate is obtained by means of hidden layer outputs.

Keywords

emotion recognition; face recognition; image classification; learning (artificial intelligence); multilayer perceptrons; MLP; artificial neurons; emotion classification; emotion identification; facial appearance; facial expressions; hidden layer outputs; multilayer NN; multilayer perceptron; neural network; nonlinear classification problems; supervised learning algorithm; Artificial neural networks; Databases; Face; Face recognition; Humans; Training; Multi layer neural network; facial expressions; image processing;

fLanguage

English

Publisher

ieee

Conference_Titel

Innovations in Intelligent Systems and Applications (INISTA), 2012 International Symposium on

Conference_Location

Trabzon

Print_ISBN

978-1-4673-1446-6

Type

conf

DOI

10.1109/INISTA.2012.6247027

Filename

6247027