A deep learning system for recognizing facial expression in real-time
| Author | Miao, Yu |
| Author | Dong, Haiwei |
| Author | Al Jaam, Jihad Mohamad |
| Author | El Saddik, Abdulmotaleb |
| Available date | 2020-06-02T08:17:30Z |
| Publication Date | 2019 |
| Publication Name | ACM Transactions on Multimedia Computing, Communications and Applications |
| Resource | Scopus |
| ISSN | 15516857 |
| Abstract | This article presents an image-based real-time facial expression recognition system that is able to recognize the facial expressions of several subjects on a webcam at the same time. Our proposed methodology combines a supervised transfer learning strategy and a joint supervision method with center loss, which is crucial for facial tasks. A newly proposed Convolutional Neural Network (CNN) model, MobileNet, which has both accuracy and speed, is deployed in both offline and in a real-time framework that enables fast and accurate real-time output. Evaluations towards two publicly available datasets, JAFFE and CK+, are carried out respectively. The JAFFE dataset reaches an accuracy of 95.24%, while an accuracy of 96.92% is achieved on the 6-class CK+ dataset, which contains only the last frames of image sequences. At last, the average run-time cost for the recognition of the real-time implementation is around 3.57ms/frame on a NVIDIA Quadro K4200 GPU. - 2019 Association for Computing Machinery. |
| Sponsor | This work was made possible by NPRP grant (10-0205-170346) from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors. Authors' addresses: Y. Miao and H. Dong, University of Ottawa, 800 King Edward Avenue, Ottawa, ON K1N 6N5, Canada; emails: {ymiao036, hdong}@uottawa.ca; J. Mohamad Al Jaam, Qatar University, Ibn Khaldoon Hall, Doha, Qatar; email: jaam@qu.edu.qa; A. El Saddik, University of Ottawa, 800 King Edward Avenue, Ottawa, ON K1N 6N5, Canada; email: elsaddik@uottawa.ca. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from permissions@acm.org. 2019 Association for Computing Machinery. 1551-6857/2019/05-ART33 $15.00 https://doi.org/10.1145/3311747 |
| Language | en |
| Publisher | Association for Computing Machinery |
| Subject | Deep learning networks Facial expression recognition |
| Type | Article |
| Issue Number | 2 |
| Volume Number | 15 |
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