EVALUATION OF AN ATTENTION BASED DIMENSIONAL EMOTION RECOGNITION - Ferreira, Antonio José da Silva; Soares, Gabriela Regina; Cardia Neto, João Baptista (Revista Interface Tecnológica, 2022)
Non-verbal feedback and the recognition of facial expressions have been an area of much research in the last decades. Facial expressions are a concrete way to recognize emotions and "teaching" computers to detect correctly what each facial expression means and to which emotion it is attached. Thus, in the scope of image recognition, Convolutional Neural Networks (CNN), through their layering over image pixels, facilitate pattern discovery. Therefore, through the application a CNN with an attention mechanism, the objective of this paper is to decode the non-verbal expressions present in the used database and identify to which emotion it is linked. Through the analysis of the CCC (Correlation Coefficient of Concordance) and the Mean Squared Error (RMSE) for the valence and arousal dimensions, this paper shows that the method used brings results, but there is still room for improvement in machine learning.