关键词: 人脸识别,表情因素,因素分解模型

Abstract: To overcome the effect of facial expression and pose on face recognition,Xu proposed using the original and “symmetrical face” training samples to perform representation based two-step face recognition.However,it usually gets bad symmetrical face samples based on mirror image with the changes of facial poses,which may affect the accuracy of recognition.A two-step face recognition algorithm based on factor decomposition model was proposed.Firstly,to reduce the effect of light,pose and other factors,the factorization model is used to separate the “expression factors” and “identity factor” from the face images which can be controlled,to construct new image samples.Meanwhile,the two-step face recognition method is adopted in the recognition stage,which makes full use of the advantage of the score level fusion,and further improves the recognition rate of the proposed algorithm.

Key words: Face recognition,Expression factor,Factorization model