Extended linear regression for undersampled face recognition
Linear Regression Classification (LRC) is extended to undersampled situation. Intraclass variant dictionary is adopted to represent training/testing variation. Quasi-inverse, ridge regularization and SVD, are designed to solve low-rank problem. Experiments show that ELRC has better generalization ability and is more robust.
linear regression face recognition intraclass variant dictionary singular value decomposition low rank undersampled classification supervised learning pattern recognition