Face Recognition Based on Locally Linear Embedding and Least Squares Support Vector Machines

In order to improve the speed of face recognition, a face recognition method based on locally linear embedding (LLE) and least squares support vector machines (LS-SVM) was proposed. After extracting the features of the pre-processing face images using principal component analysis (PCA) and locally linear embedding, LS-SVM was used to train the feature sets and recognize the faces. And, the speed of face recognition was improved. Finally, the method was tested on the ORL (Olivetti Research Laboratory) face database, the results show that the proposed method can improve the speed of face recognition, and the rate of face recognition exceeds 90%.