Proceedings of the 7th Mathematics, Science, and Computer Science Education International Seminar, MSCEIS 2019, 12 October 2019, Bandung, West Java, Indonesia

Research Article

Facial Expression Recognition on The Classroom Environments

Download484 downloads
  • @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
Wawan Setiawan1,*, Yaya Wihardi1, Enjun Junateti1, Naufan Rusyda Faikar1
  • 1: Universitas Pendidikan Indonesia, Jl. Dr. Setiabudhi 229, Bandung, Indonesia
*Contact email: wawans@upi.edu

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.