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Classifying Emotion based on Facial Expression Analysis using Gabor Filter: A Basis for Adaptive Effective Teaching Strategy

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Computational Science and Technology

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 603))

Abstract

Emotion is equivalent to mood or state of human emotion that correlates with non-verbal behavior. Related literature shows that humans tend to give off a clue for a particular feeling through nonverbal cues such as facial expression. This study aims to analyze the emotion of students using Philippines-based corpus of a facial expression such as fear, disgust, surprised, sad, anger and neutral with 611 examples validated by psychology experts and results aggregates the final emotion, and it will be used to define the meaning of emotion and connect it with a teaching pedagogy to support decisions on teaching strategies. The experiments used feature extraction methods such as Haar-Cascade classifier for face detection; Gabor filter and eigenfaces API for features extraction; and support vector machine in training the model with 80.11% accuracy. The result was analyzed and correlated with the appropriate teaching pedagogies for educators and suggest that relevant interventions can be predicted based on emotions observed in a lecture setting or a class. Implementing the prototype in Java environment, it captured images in actual class to scale the actual performance rating and had an average accuracy of 60.83 %. It concludes that through aggregating the facial expressions of students in the class, an adaptive learning strategy can be developed and implemented in the classroom environment.

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Author information

Authors and Affiliations

  1. Saint Michael’s College of Laguna, Binan, Philippines

    Anna Liza A. Ramos

  2. Technological Institute of the Philippines, Manila, Philippines

    Bryan G. Dadiz

  3. Asiatech-Sta. Rosa, City of Sta. Rosa, Laguna, Philippines

    Arman Bernard G. Santos

Authors
  1. Anna Liza A. Ramos
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  2. Bryan G. Dadiz
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  3. Arman Bernard G. Santos
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Corresponding author

Correspondence to Anna Liza A. Ramos .

Editor information

Editors and Affiliations

  1. Knowledge Technology Research Unit, Faculty of Computing and Informatics, Universiti Malaysia Sabah, Kota Kinabalu, Malaysia

    Rayner Alfred

  2. School of Information Science, Security and Networks Area, Japan Advanced Institute of Science and Technology, Ishikawa, Japan

    Yuto Lim

  3. Department of Computer Science, Universitas Mulawarman, Samarinda, Indonesia

    Haviluddin Haviluddin

  4. Center of Data and Information Management, Universiti Malaysia Sabah, Kota Kinabalu, Sabah, Malaysia

    Chin Kim On

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© 2020 Springer Nature Singapore Pte Ltd.

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Ramos, A.L.A., Dadiz, B.G., Santos, A.B.G. (2020). Classifying Emotion based on Facial Expression Analysis using Gabor Filter: A Basis for Adaptive Effective Teaching Strategy. In: Alfred, R., Lim, Y., Haviluddin, H., On, C. (eds) Computational Science and Technology. Lecture Notes in Electrical Engineering, vol 603. Springer, Singapore. https://doi.org/10.1007/978-981-15-0058-9_45

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  • DOI: https://doi.org/10.1007/978-981-15-0058-9_45

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-0057-2

  • Online ISBN: 978-981-15-0058-9

  • eBook Packages: EngineeringEngineering (R0)

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