BROWSE
Detail
Conference Paper
Real-Time Personalized Facial Expression Recognition System based on Deep Learning
Cited 17 time in 
Share 
Share
- Authors
- Injae Lee, Heechul Jung, Chung Hyun Ahn, Jeongil Seo, Junmo Kim, Ohseok Kwon
- Issue Date
- 2016-01
- Citation
- International Conference on Consumer Electronics (ICCE) 2016, pp.267-268
- Publisher
- IEEE
- Language
- English
- Type
- Conference Paper
- Abstract
- 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.
- KSP Keywords
- Application fields, Behavior research, Consumer behavior, Facial Expression Recognition(FER), Facial expression recognition system, Feature-based methods, Hand-crafted feature, High accuracy, Human Emotions, Market Research, Real-Time