Face Recognition Algorithm Based on Weighted Neighborhood Maximum Margin Discriminant Embedding
摘要
Based on Local Maximal Margin Discriminant Embedding(LMMDE) method,an algorithm named Weighted Neighborhood Maximum Margin Discriminant Embedding(WNMMDE) is proposed.This algorithm is a feature extraction algorithm based on manifold.It preserves the neighborhood geometry structure of the data while constructing objective function by optimal reconstruction coefficient of data.At the same time,the algorithm does not need to compute the inverse of the high dimension matrix,and it can overcome the small sample problem in feature extraction.Recognition experimental results on two general face image database show that the proposed algorithm makes full use of the discriminant information of each manifold,minimizes the distance between the same class of neighboring nodes as far as possible,increases the distance between different classes of neighboring nodes,which effectively distinguishes different categories,and can get better recognition results.