An age-span face recognition method based on an NMF algorithm with sparseness constraints
Yong-Qing Ye · Caai Transactions on Intelligent Systems · 2012
For face recognition technology,apart from lighting,gesture,and expression factors,variations in shape and texture of human faces due to aging factors also significantly affect the performance of face recognition systems.Using a sparse-constrained non-negative matrix factorization(NMF) algorithm,a facial aging simulation method based on an improved prototype was first proposed and then applied to age-span face recognition to add virtual samples and heighten the recognition rate.Experimental results show that the age span indeed has a great effect on face recognition;the NMF algorithm has stronger feature extraction ability when the coefficient matrix is sparsely constrained.Furthermore,the recognition ratio is apparently improved after adding additional virtual samples by aging simulation of face texture features.