Abstract
Facial expression is the most powerful and natural non-verbal emotional communication method. Facial Expression Recognition(FER) has significance in machine learning tasks. Deep Learning models perform well in FER tasks, but it doesn't provide any justification for its decisions. Based on the hypothesis that facial expression is a combination of facial muscle movements, we find that Facial Action Coding Units(AUs) and Emotion label have a relationship in CK+ Dataset. In this paper, we propose a model which utilises AUs to explain Convolutional Neural Network(CNN) model's classification results. The CNN model is trained with CK+ Dataset and classifies emotion based on extracted features. Explanation model classifies the multiple AUs with the extracted features and emotion classes from the CNN model. Our experiment shows that with only features and emotion classes obtained from the CNN model, Explanation model generates AUs very well.
Original language | English |
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Title of host publication | 2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019 - Proceedings |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Electronic) | 9781538677896 |
DOIs | |
Publication status | Published - 2019 Apr 1 |
Event | 2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019 - Kyoto, Japan Duration: 2019 Feb 27 → 2019 Mar 2 |
Publication series
Name | 2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019 - Proceedings |
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Conference
Conference | 2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019 |
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Country/Territory | Japan |
City | Kyoto |
Period | 19/2/27 → 19/3/2 |
Bibliographical note
Funding Information:This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Science, ICT & Future Planning(NRF-2017R1A2B4003558)
Publisher Copyright:
© 2019 IEEE.
Keywords
- Deep learning
- Explanation Model
- Facial Action Coding System
- Facial Expression Recognition
- Justification
ASJC Scopus subject areas
- Information Systems and Management
- Artificial Intelligence
- Computer Networks and Communications
- Information Systems