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Video-based Facial Emotion Recognition using Active Shape Models and Statistical Pattern Recognizers

Journal: The Journal of the Institute of Internet, Broadcasting and Communication (Vol.14, No. 2)

Publication Date:

Authors : ; ; ; ;

Page : 139-146

Keywords : Emotion recognition; Facial expression; ASM (activa shape model); Pattern recognition; SVM (support vector machine).;

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Abstract

This paper proposes an efficient method for automatically distinguishing various facial expressions. To recognize the emotions from facial expressions, the facial images are obtained by digital cameras, and a number of feature points were extracted. The extracted feature points are then transformed to 49-dimensional feature vectors which are robust to scale and translational variations, and the facial emotions are recognized by statistical pattern classifiers such Naive Bayes, MLP (multi-layer perceptron), and SVM (support vector machine). Based on the experimental results with 5-fold cross validation, SVM was the best among the classifiers, whose performance was obtained by 50.8% for 6 emotion classification, and 78.0% for 3 emotions.

Last modified: 2016-01-29 13:13:59