Geometric feature based facial expression recognition using multiclass support vector machines

In this paper, a novel Geometric features extraction method for facial expression recognition is proposed. ASM automatic fiducial point location algorithm is firstly applied to a facial expression image, and then calculating the Euclidean distances between the center of gravity coordinate and the annotated fiducial points' coordinates of the face image. In order to extract the discriminate deformable geometric information, the system extracts the geometric deformation difference features between a person's neural expression and the other seven basic expressions. A multiclass Support Vector Machine (SVM) classifier is used to recognize the facial expressions. Experiments indicate that our proposed method can obtain good classification accuracy.