intelligent systems
A. V. Atanasov, D. Pilev, F. Tomova. Bimodal System for Emotion Recognition Based on Deep Neural Networks

Key Words: Online Learning; Deep Neural Networks; Face Recognition; Facial Emotions Recognition; Python.

Abstract. Current study presents development of bimodal system for Facial Emotion Recognition (FER) and Body Gestures Emotion Recognition (BER). The system is based on two Deep Learning Neural Networks (DNN) each one responsible for the recognition of the emotion of the face or the body. The use of the combination of two neural networks has an amplifying synergistic effect, which increases by about 10% the accuracy of the results (recognized emotionс) compared to those of the individual DNN. The selection of pre-trained DNN models for facial and body emotions recognition is based on two authors’ papers, in which detailed analysis of the DNN for FER and BER has been done. Therefore in current study a brief information about selected DNN models is provided, as well information about specific dataset used for training selected DNNs. Verification of the bimodal system is done using our private dataset.