Intelligent Emotion Evaluation Method of Classroom Teaching Based on Expression Recognition

Yanqiu Liang


To solve the problem of emotional loss in teaching and improve the teaching effect, an intelligent teaching method based on facial expression recognition was studied. The traditional active shape model (ASM) was improved to extract facial feature points. Facial expression was identified by using the geometric features of facial features and support vector machine (SVM). In the expression recognition process, facial geometry and SVM methods were used to generate expression classifiers. Results showed that the SVM method based on the geometric characteristics of facial feature points effectively realized the automatic recognition of facial expressions. Therefore, the automatic classification of facial expressions is realized, and the problem of emotional deficiency in intelligent teaching is effectively solved.


intelligent teaching; emotion recognition; support vector machine (SVM)

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Copyright (c) 2019 Yanqiu Liang

International Journal of Emerging Technologies in Learning (iJET) – eISSN: 1863-0383
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