Face recognition based on a new feature extraction method
Zhu Shan-an · Guangdian gongcheng · 2007
In view of the discriminant feature extraction problem in face recognition, a new face image feature extraction and recognition method— Extended Locality Preserving Projections (ELPP) is proposed in this paper. When constructing graphs, LPP emphasizes face sample manifold local structure belongs to unsupervised learning algorithms. By using turning parameter, ELPP combines both the face manifold local structure information and class label information, and extracts the discriminant feature of face for recognition. The proposed method was tested and evaluated in the Yale face database and ATT face database. Nearest Neighborhood (NN) algorithm was used to construct classifiers. The experimental results show that ELPP has good performance when pose, lighting condition, face expression and train sample number change.