Sparsity Preserving-Based Local Fisher Discriminant Analysis with Applications in Face Recognition
Changbin Li · 2012
A kind of algorithm called sparsity preserving-based local fisher discriminant analysis (SPLFDA) is proposed, which insulates sparsity preserving projections and local fisher discriminant analysis in the process of dimensionality reduction. It inherits the special character of geometrical structure preserving and neighborhood preserving. Experiments operated on UMIST, Yale and YaleB face dataset show that the algorithm is more effective.