Facial Expression Recognition Based on Graph Neural Network
Xu Xu, Zhou Ruan, Lei Yang
Abstract
Facial expressions are one of the most powerful, natural and immediate means for human being to present their emotions and intensions. In this paper, we present a novel method for fully automatic facial expression recognition. The facial landmarks are detected for characterizing facial expressions. A graph convolutional neural network is proposed for feature extraction and facial expression recognition classification. The experiments were performed on the three facial expression databases. The result shows that the proposed FER method can achieve good recognition accuracy up to 95.85% using the proposed method.
Topics & Concepts
Computer scienceFacial expressionArtificial intelligenceConvolutional neural networkPattern recognition (psychology)Feature extractionFacial expression recognitionFacial recognition systemGraphFeature (linguistics)Artificial neural networkSpeech recognitionTheoretical computer scienceLinguisticsPhilosophyFace and Expression RecognitionEmotion and Mood RecognitionFace recognition and analysis