Research Area:  Machine Learning

Abstract:

Facial expression recognition (FER) enables computers to understand human emotions and is the basis and prerequisite for quantitative analysis of human emotions. As a challenging interdisciplinary in biometrics and emotional computing, FER has become a research hotspot in the field of pattern recognition, computer vision and artificial intelligence both at home and abroad. As a new machine learning theory, deep learning not only emphasizes the depth of learning model, but also highlights the importance of feature learning for network model, and has made some research achievements in facial expression recognition. In this paper, the current research states are analyzed mostly from the latest facial expression extraction algorithm and the FER algorithm based on deep learning a comparison is made of these methods. Finally, the research challenges are generally concluded, and the possible trends are outlined.

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Author(s) Name:  Ting Zhang

Publisher name:  Springer

DOI:  10.1007/978-3-319-69096-4_48

Volume Information:  

Paper Link:   https://link.springer.com/chapter/10.1007/978-3-319-69096-4_48