Face Recognition Based on Two-dimensional Locality Preserving Projections
Zhu Shan-an · 2007
Feature extraction is an important step of face recognition.To extract discriminant feature effectively is the key point for a good face recognition algorithm.Normally the face recognition algorithm is based on the image vector which is converted from the image matrix.A new face image feature extraction and recognition method based on two-dimensional locality preserving projections(2DLPP) was proposed in this paper.2DLPP works directly with images in their native state-two dimensional matrices,and extracts the two-dimensional discriminant feature of face for recognition based on both the face manifolalocal structure information and the labels' information.The proposed method was tested and evaluated with the ATT face database,where the nearest neighborhood(NN) algorithm was used to construct classifiers,and the experimental results show that 2DLPP is more powerful than the PCA,LDA and LPP for face feature extraction and recognition.