Enhanced LLE Features Classification for Face Recognition

A face recognition method is proposed using large margin nearest neighbor (LMNN) algorithm to improve locally linear embedding (LLE) features classification performance. LMNN is used to seek a linear transformation by which the Euclidean distance in the transformation space could equivalently be viewed as Mahalanobis distances in the original space. Hence, the kNN classification performance could be improved. Experiments on ORL database and extended YaleB database demonstrate the effectiveness of the proposed method.