Name
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 similar to 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. |
Year | Venue | Field |
|---|---|---|
2016 | 2016 IEEE INTERNATIONAL CONFERENCE ON CONSUMER ELECTRONICS (ICCE) | Computer vision,Sadness,Facial recognition system,Disgust,Computer science,Usability,Facial expression,Happiness,Artificial intelligence,Deep learning,Surprise |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Injae Lee | 1 | 0 | 1.01 |
| Heechul Jung | 2 | 208 | 10.24 |
| Chunghyun Ahn | 3 | 9 | 1.56 |
| Jeongil Seo | 4 | 0 | 0.34 |
| Junmo Kim | 5 | 476 | 42.50 |
| Ohseok Kwon | 6 | 0 | 0.34 |