| Title | Real-Time Facial Expression Recognition Based on CNN |
| Publication Type | Conference Paper |
| Year of Publication | 2019 |
| Authors | Liu, Keng-Cheng, Hsu, Chen-Chien, Wang, Wei-Yen, Chiang, Hsin-Han |
| Conference Name | 2019 International Conference on System Science and Engineering (ICSSE) |
| Keywords | average weighting method, CNN, convolution, convolution neural network, convolution neural network (CNN), convolutional neural nets, emotion recognition, face recognition, facial expression recognition, facial recognition, feature extraction, high speed capturing, Human Behavior, human facial expression, image characteristics, image preprocessing, image recognition, incorrect recognition, Metrics, Neural networks, pubcrawl, real-time facial expression recognition, Real-time Systems, recognition speed, Resiliency, Training, training framework, Webcams |
| Abstract | In this paper, we propose a method for improving the robustness of real-time facial expression recognition. Although there are many ways to improve the accuracy of facial expression recognition, a revamp of the training framework and image preprocessing allow better results in applications. One existing problem is that when the camera is capturing images in high speed, changes in image characteristics may occur at certain moments due to the influence of light and other factors. Such changes can result in incorrect recognition of the human facial expression. To solve this problem for smooth system operation and maintenance of recognition speed, we take changes in image characteristics at high speed capturing into account. The proposed method does not use the immediate output for reference, but refers to the previous image for averaging to facilitate recognition. In this way, we are able to reduce interference by the characteristics of the images. The experimental results show that after adopting this method, overall robustness and accuracy of facial expression recognition have been greatly improved compared to those obtained by only the convolution neural network (CNN). |
| DOI | 10.1109/ICSSE.2019.8823409 |
| Citation Key | liu_real-time_2019 |
Real-Time Facial Expression Recognition Based on CNN