3D facial expression recognition based on variation faces
Xiaoli Li, Qiuqi Ruan, Gaoyun An, Chengxiong Ruan · 2012
Automatic 3D facial expression recognition is still a challenging problem. This paper proposes the variation faces combining SVM to classify 3D facial expressions automatically as the flow of generating variation faces is without any manual intervention. To validate this strategy, the Fourier spectrum feature is explored and its highest recognition rate, 85.33% represents to be comparative to most primary work. Avoiding the irregularity of the3D facial models is the most valuable thing of the variation faces which opens a promising direction for automatic 3D facial expression recognition.