2DR1-PCA and 2DL1-PCA: two variant 2DPCA algorithms based on none L2 norm
This is an incremental improvement for face recognition systems, addressing outlier sensitivity in existing methods.
The paper tackled face recognition by proposing 2DR1-PCA and 2DL1-PCA, two variants of 2DPCA based on R1 and L1 norms, which are less sensitive to outliers, and tested them on ORL, YALE, and XM2VTS databases with experimental comparisons.
In this paper, two novel methods: 2DR1-PCA and 2DL1-PCA are proposed for face recognition. Compared to the traditional 2DPCA algorithm, 2DR1-PCA and 2DL1-PCA are based on the R1 norm and L1 norm, respectively. The advantage of these proposed methods is they are less sensitive to outliers. These proposed methods are tested on the ORL, YALE and XM2VTS databases and the performance of the related methods is compared experimentally.