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. 3)Publication Date: 2014-06-30
Authors : Gil-Jin Jang; Ahra Jo; Jeong-Sik Park; Yong-Ho Seo;
Page : 139-146
Keywords : Emotion recognition; Facial expression; ASM (activa shape model); Pattern recognition; SVM (support vector machine);
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.
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