Copyright (C) 2023 Jing Wang

RSSPCA finds the first projection vector by solving the following optimization problem: $$\mathop{\max}_{w}||X^Tw||_1, s.t. ||w||_2^2=1, ||w||_1<=c_1, w^TLw<=c_2,$$ where $c_1$ and $c_2$ are positive constants, $L$ is a Laplacian matrix representing the two-dimensional spatial structure information of images.

Experiments were conducted on six benchmark face databases including the AR, FEI, FERET, GT, ORL, and Yale face databases. More benchmark face databases are refered to: https://github.com/yuzhounh/Face_databases.

Five competing algorithms including PCA, PCA-L1, RSPCA, and RSMPCA were compared with the proposed RSSPCA in terms of face reconstruction and recognition.

This repository is a parallel computing version of the original code: https://github.com/yuzhounh/RSSPCA.

Run main.m to play this demo.

Jing Wang
[email protected]
2024-1-29 12:31:24