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Published in:
2020 | OriginalPaper | Chapter
Real-Time Expression Recognition Improvement System Based on Deep Learning
Authors : Lianghui Zhao, Yingdong Wu, Xixi Zhu, Wanting He
Published in: Innovative Computing
Publisher: Springer Singapore
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Abstract
Expression recognition is a relatively new direction in the field of face recognition, and the knowledge involved is not only unilateral, but its in-depth research has brought benefits to the development of artificial intelligence and even to human life. In response to this, this paper intends to design an improved real-time facial expression recognition system. The design first uses a deep learning method to design a facial expression recognition model, and then embeds the OpenCV framework and the cascading face detector of the Dlib open source library, and combines the ORB feature extraction algorithm to achieve real-time detection and recognition of facial expressions. To identify robustness, this study has achieved certain results in practice. The research has certain help in the fields of psychology and education, such as the feedback of classroom students’ teaching quality and the analysis of people’s real-time expressions. The dataset used in the study was the fer2013 facial expression dataset.