Facial expression recognition using moment invariants and singular value decomposition

This paper proposes a method of facial expressions recognition which combined moment invariants features with singular value. Moment invariants and singular value features are extracted respectively from the eyes, eyebrows and mouth regions in the facial expression images. Then these features are optimized to obtain a feature vector by Fisher linear discriminate analysis and a SVM classifier is trained as recognition. The experiments results show that the method can improve the recognition rate and has robust performance.