| Title | Multi-user facial emotion recognition in video based on user-dependent neural network adaptation |
| Publication Type | Conference Paper |
| Year of Publication | 2022 |
| Authors | Churaev, Egor, Savchenko, Andrey V. |
| Conference Name | 2022 VIII International Conference on Information Technology and Nanotechnology (ITNT) |
| Date Published | may |
| Keywords | Adaptation models, convolutional neural networks, Convolutional Neural Networks (CNN), Deep Learning, emotion recognition, face recognition, facial analysis, facial emotion recognition, facial recognition, fine-tuning, Human Behavior, Metrics, Neural networks, pubcrawl, resilience, Resiliency, Speech recognition, Training |
| Abstract | In this paper, the multi-user video-based facial emotion recognition is examined in the presence of a small data set with the emotions of end users. By using the idea of speaker-dependent speech recognition, we propose a novel approach to solve this task if labeled video data from end users is available. During the training stage, a deep convolutional neural network is trained for user-independent emotion classification. Next, this classifier is adapted (fine-tuned) on the emotional video of a concrete person. During the recognition stage, the user is identified based on face recognition techniques, and an emotional model of the recognized user is applied. It is experimentally shown that this approach improves the accuracy of emotion recognition by more than 20% for the RAVDESS dataset. |
| DOI | 10.1109/ITNT55410.2022.9848645 |
| Citation Key | churaev_multi-user_2022 |
Multi-user facial emotion recognition in video based on user-dependent neural network adaptation