[Article] Emotion recognition based on convolutional neural networks and heterogeneous bio-signal data sources.
summary : This paper uses multi-modal bio-signals such as EEG, Eye data (Pupil diameter, eye gaze coordinates), and Facial data (using a depth camera) to recognize an individual’s emotions in valence and arousal. This paper suggests the multi-branch convolutional neural network (MBCNN) which shows the best accuracy among the state-of-the-art models while using multi-modal data, especially depth data.