전이 학습을 이용한 얼굴 감정 인식 비전 기반 딥러닝 알고리즘 비교 연구

초록

In this research, we have explored state-of-the-art deep learning algorithms for face emotion recognition. In this regard, we implement transfer learning for seven classes of emotions using traditional deep learning algorithms for image classifications such as MobileNetv2, GoogleNet, ResNet101, VGGNet19. In addition, we also compared our results with a specially designed deep learning model for face emotion recognition such as “Deep Emotion”. We have utilized the dataset FER2013 published by google and has been exploited by many researchers. We have analyzed the accuracy, time of training, complexity in terms of layers, and other parameters. After training on FER2013, we have deployed each model on a Korean dataset obtained from Korean dramas videos containing images of celebrities. Our ultimate goal was to label all unknown Korean dataset after training on FER2013. We have presented three different programs i.e. (i) automatic labeling, (ii) transfer learning-based models for unknown images, (iii) deep-emotion model for face emotion recognition. We have presented a detailed analysis of all models and our corresponding programs