Volume 3, Issue 1, June 2016, Pages 9 - 12
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
- 10.2991/jrnal.2016.3.1.3How to use a DOI?
- 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 Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - JOUR AU - Taiki Nishime AU - Satoshi Endo AU - Koji Yamada AU - Naruaki Toma AU - Yuhei Akamine PY - 2016 DA - 2016/06/01 TI - Feature Acquisition From Facial Expression Image Using Convolutional Neural Networks JO - Journal of Robotics, Networking and Artificial Life SP - 9 EP - 12 VL - 3 IS - 1 SN - 2352-6386 UR - https://doi.org/10.2991/jrnal.2016.3.1.3 DO - 10.2991/jrnal.2016.3.1.3 ID - Nishime2016 ER -