A 3D Facial Expression Recognition System Based On SVM Classifier Using Distance Based Features - Soylemez, Omer Famk; Ergen, Burhan; Hark Soylemez, Nesrin (Ieee, 2017)
In this study, an SVM-based system is proposed for the classification of facial expressions that are represented in 3D. Distance based features are used as a feature vector, which are determined by the distances between the different key points on the image. Study was conducted on a subset (Happy, sadness, surprise) of Bosphorus 3D Face Database. 9 different fiducial points arc used to calculate a total of 5 distance features. SVM classification was performed with K-fold cross validation thus mean classification performance of different training and test clusters were determined. %85 success rate has achieved as a result of the expression analysis performed on the 3D facial scans.
Mesafe Tabanli Özellikleri Kullanan SVM Tabanli bir 3B Yüz İfade Tanima Sistemi
25th Signal Processing and Communications Applications Conference (SIU) -- MAY 15-18, 2017 -- Antalya, TURKEY
Keywords: Facial expression recognition; Distance based Features; Support vector machines