Analysis and Implementation of Optimization Techniques for Facial Recognition

Table 10

Recognition accuracy of other methods on the YaleB and AT&T datasets.

Author	Method	Recognition accuracy (%)	Database
[32]	Generalized low-rank approximation of matrices (GLRAM)	82.18	YaleB
[33]	FDDL	96.2	YaleB
[34]	Local nonlinear multilayer contrast patterns (LNLMCP)	97.50	YaleB
[35]	Discriminative sparse representation via 2 regularization	82.61	YaleB
[32]	GLRAM	97.25	AT&T
[33]	Fisher discriminative dictionary learning (FDDL)	96.7	AT&T
[31]	PSO–KNN	98.75	AT&T
[31]	PCA-LDA fusion algorithm	98.00	AT&T
[35]	Discriminative sparse representation via 2 regularization	95.00	AT&T