Personalized facial expression recognition in indoor environments

Facial expression recognition is one of the most popular topics in emotion analysis. Most facial expression recognition systems are implemented using general expression models. Since facial expressions may be expressed differently by different people, inaccurate results are unavoidable. The proposed facial expression recognition system recognizes facial expressions using the facial features of an individual user. A radial basis function neural network is applied to classify seven emotions: neutral, happy, angry, surprised, sad, scared, and disgusted. Experiment results show that the proposed system can accurately identify emotions from facial expressions.