Model Representation for Facial Expression Recognition Based on Shape and Texture
Adriana Cruz de Gois, Victor Oliveira Antonino, Tsang Ing Ren, George D. C. Cavalcanti · 2012
In this paper, we present an efficient method for facial expression recognition. Three features extraction methods are combined to form a model representation for facial expressions. Once the feature and the model representation are defined a Support Vector Machine (SVM) is used for the classification task. The proposed method is tested using the Yale and Cohn-Kanade databases, which contains 165 images and 1480 images, respectively. The method presented a recognition rate of 98.1% and 93% for the Yale and Cohn-Kanade respectively.