Human Perception Mechanism based CNN-RNN Framework for Dimensional Emotion Recognition

In this paper, we propose human perception mechanism based CNN-RNN based approach to recognize dimensional emotion using Aff-Wild dataset. The proposed model recognizes dimensional expression through two steps. First, motivated by the human facial expression perception mechanism, the patches were extracted based on facial key points. Second, the facial expression was classified based on CNN-RNN model using extracted patches. The mean concordance correlation coefficient (CCC) of the proposed model is 0.322, indicating superior performance compared to the original CNN-RNN model, which achieved a mean CCC of 0.283.