Research Article
Facial Expression Recognition on The Classroom Environments
@INPROCEEDINGS{10.4108/eai.12-10-2019.2296519, author={Wawan Setiawan and Yaya Wihardi and Enjun Junateti and Naufan Rusyda Faikar}, title={Facial Expression Recognition on The Classroom Environments}, proceedings={Proceedings of the 7th Mathematics, Science, and Computer Science Education International Seminar, MSCEIS 2019, 12 October 2019, Bandung, West Java, Indonesia}, publisher={EAI}, proceedings_a={MSCEIS}, year={2020}, month={7}, keywords={facial expression gcns gabor filter mood detection}, doi={10.4108/eai.12-10-2019.2296519} }- Wawan Setiawan
Yaya Wihardi
Enjun Junateti
Naufan Rusyda Faikar
Year: 2020
Facial Expression Recognition on The Classroom Environments
MSCEIS
EAI
DOI: 10.4108/eai.12-10-2019.2296519
Abstract
Facial expression recognition is the process of identifying the expression that is displayed by a person. It can be used to evaluate the mood of students during a class so that can help teachers improve the learning goal achievement. However, the recognition process in real environments such as in classrooms is still a challenging problem due to different expressions and illumination under arbitrary poses. In this paper, we present a convolutional neural network-based method that combining with Gabor filter. The result shows that the proposed method can recognize three categories of student facial expressions that represent a good, bad, and neutral expression.
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