Facial Expression Recognition Based on FSVM and KNN

To improve the recognition accuracy,a new approach for facial expression recognition based on Fuzzy Support Vector Machine (FSVM) and K-Nearest Neighbor (KNN) is presented in this paper.At first,the feature of the static facial expression image is extracted by the Principle Component Analysis (PCA),then,the algorithm divide the region into different types,and combine with the characteristic of the FSVM and KNN,switch the classification methods to the different types.The result of the experiment show that proposed algorithm can achieve good recognition accuracy,and can simplify the computation complexity.