Feature Acquisition From Facial Expression Image Using Convolutional Neural Networks

Authors
Taiki Nishime, Satoshi Endo, Koji Yamada, Naruaki Toma, Yuhei Akamine
Corresponding Author
Taiki Nishime
Available Online 1 June 2016.
DOI
https://doi.org/10.2991/jrnal.2016.3.1.3
Keywords
facial expression recognition, convolutional neural networks, deep learning, feature learning
Abstract
In this study, we carried out the facial expression recognition from facial expression dataset using Convolutional Neural Networks (CNN). In addition, we analyzed intermediate outputs of CNN. As a result, we have obtained a emotion recognition score of about 58%; two emotions (Happiness, Surprise) recognition score was about 70%. We also confirmed that specific unit of intermediate layer have learned the feature about Happiness. This paper details these experiments and investigations regarding the influence of CNN learning from facial expression.

Copyright
© 2013, the Authors. Published by ALife Robotics Corp. Ltd.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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