Visible to the public Facial Expression Recognition Based on Graph Neural Network

TitleFacial Expression Recognition Based on Graph Neural Network
Publication TypeConference Paper
Year of Publication2020
AuthorsXu, X., Ruan, Z., Yang, L.
Conference Name2020 IEEE 5th International Conference on Image, Vision and Computing (ICIVC)
Keywordsconvolutional neural nets, convolutional neural networks, Databases, emotion recognition, emotions, Face, face landmarks detection, face recognition, facial expression databases, facial expression recognition, facial expression recognition classification, facial landmark detection, facial recognition, feature extraction, fully automatic facial expression recognition, graph convolutional neural network, Graph Neural Network, graph theory, Human Behavior, image classification, image recognition, Metrics, object detection, pubcrawl, resilience, Resiliency, Support vector machines

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.

Citation Keyxu_facial_2020