To solve the problem of calculating efficiency in the process of facial recognition

the principal component analysis（PCA） method is used to select the features of the image

however

the calculation efficiency of traditional PCA depends on the size of the dimension. In order to speed up the calculation speed

a fast PCA algorithm（FastPCA） is given. FastPCA can effectively reduce the time of feature extraction. A face recognition method is presented by twin support vector machine（TWSVM） based on AdaBoost

which can improve recognition accuracy and avoid over fitting. Simulation experiments ae conducted on the ORL and Yale face databases. The experimental results show that the proposed method has better recognition rate and higher feature extraction efficiency.