An Emotion Recognition Model Using Facial Expressions in Distance Learning

Year 2022, Volume: 11 Issue: 3, 770 - 778, 30.09.2022

Beyza Esin Özseven , Naim Cagman

https://doi.org/10.17798/bitlisfen.1079499

Abstract

The most important factor on the success of the student is the student's readiness for the lesson, motivation, cognitive and emotional state. In face-to-face education, the educator can follow the student visually throughout the lesson and can observe his emotional state. One of the most important disadvantages of distance learning is that the emotional state of the student cannot be followed instantly. In addition, the processing time of emotion detection, in which real-time emotion detection will be performed, should be short. In this study, a method for emotion recognition is proposed by using distance and slope information between facial landmarks. In addition, the feature size was reduced by detecting only those that are effective for emotion recognition among the distance and slope information with statistical analysis. According to the results obtained, the proposed method and feature set achieved 86.11% success. In addition, the processing time is at a level that can be used in distance learning and can detect real-time emotion.

Keywords

Distance learning, emotion recognition, facial expression, emotion classification, emotional analysis

Uzaktan Eğitimde Yüz İfadeleri Kullanılarak Duygu Tanıma Modeli

Abstract

Öğrenci başarısı üzerindeki en önemli etken öğrencinin derse hazır bulunuşluğu, motivasyonu, bilişsel ve duygusal durumudur. Yüz yüze gerçekleştirilen eğitimde eğitimci öğrenciyi ders boyunca görsel olarak takip edebilmekte ve duygusal durumu ile ilgili gözlemde bulunabilmektedir. Uzaktan eğitimdeki en önemli dezavantajlardan birisi öğrencinin duygusal durumunun anlık olarak takip edilememesidir. Ayrıca, gerçek zamanlı duygu tespiti gerçekleştirileceği için duygu tespiti işlem süresinin kısa olması gereklidir. Bu çalışmada, yüz noktaları arasındaki uzaklık ve eğim bilgisi kullanılarak duygu tespiti için yöntem önerilmiştir. Ayrıca, istatistiksel analiz ile uzaklık ve eğim bilgilerinden sadece duygu tespiti üzerinde etkili olanlar tespit edilerek öznitelik boyutu azaltılmıştır. Elde edilen sonuçlara göre önerilen yöntem ve öznitelik kümesi %86.11 başarı sağlamıştır. Ayrıca, işlem süresi uzaktan eğitimde kullanılabilecek ve gerçek zamanlı duygu tespiti yapabilecek seviyededir.

Keywords

Uzaktan eğitim, duygu tespiti, yüz ifadesi, duygu sınıflandırma, duygusal analiz

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