TY - GEN
T1 - Real-time personalized facial expression recognition system based on deep learning
AU - Lee, Injae
AU - Jung, Heechul
AU - Ahn, Chung Hyun
AU - Seo, Jeongil
AU - Kim, Junmo
AU - Kwon, Ohseok
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/3/10
Y1 - 2016/3/10
N2 - Over the last few years, deep learning has produced breakthrough results in many application fields including speech recognition, image understanding and so on. We try to deep learning techniques for real-time facial expression recognition instead of hand-crafted feature-based methods. The proposed system can recognize human emotions based on facial expressions using a webcam. It can detect faces and recognize users with a distance of 2∼3m for TV environment. And it can determine whether a user is feeling happiness, sadness, surprise, anger, disgust, neutral or any combination of those six emotions. The experimental results show that the proposed method achieves high accuracy. It can be used for various services such as consumer behavior research, usability studies, psychology, educational research, and market research.
AB - Over the last few years, deep learning has produced breakthrough results in many application fields including speech recognition, image understanding and so on. We try to deep learning techniques for real-time facial expression recognition instead of hand-crafted feature-based methods. The proposed system can recognize human emotions based on facial expressions using a webcam. It can detect faces and recognize users with a distance of 2∼3m for TV environment. And it can determine whether a user is feeling happiness, sadness, surprise, anger, disgust, neutral or any combination of those six emotions. The experimental results show that the proposed method achieves high accuracy. It can be used for various services such as consumer behavior research, usability studies, psychology, educational research, and market research.
UR - http://www.scopus.com/inward/record.url?scp=84965166834&partnerID=8YFLogxK
U2 - 10.1109/ICCE.2016.7430609
DO - 10.1109/ICCE.2016.7430609
M3 - Conference contribution
AN - SCOPUS:84965166834
T3 - 2016 IEEE International Conference on Consumer Electronics, ICCE 2016
SP - 267
EP - 268
BT - 2016 IEEE International Conference on Consumer Electronics, ICCE 2016
A2 - Bellido, Francisco J.
A2 - Diaz-Sanchez, Daniel
A2 - Vun, Nicholas C. H.
A2 - Dolar, Carsten
A2 - Ling, Wing-Kuen
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - IEEE International Conference on Consumer Electronics, ICCE 2016
Y2 - 7 January 2016 through 11 January 2016
ER -
