Cost-sensitive Sparse Locality Preserving Projections
Lin Kezhen · Harbin Ligong Daxue xuebao · 2015
In Locality Preserving Projections algorithm,faces in similar categories are projected as the same one,leading to the decrease of recognition rate. To solve this problem,Cost-sensitive Sparse Locality Preserving Projections algorithmbased on LPP algorithm is proposed. In CSLPP algorithm,in which Cost-Sensitive Learning was applied to face recognition,face samples were first cost-sensitively thought of,and Sparseness,at last the optimal projection vector was figured out. Experimental results on the YALE and FERET face databases show that CSLPP algorithm effectively avoids high risks and its recognition rate is significantly higher than that of others in Nearest Neighbor Classifier.