Discriminative kernel sparse representation via l 2 regularisation for face recognition
Keqi Wang, Haifeng Hu, Tun-Dong Liu · Electronics Letters · 2018
A kernel‐based discriminative sparse representation method (KDSR) via l 2 ‐norm regularisation for robust face recognition is proposed. Sparse representation in the original sample space is usually a linear representation which does not consider the non‐linear relationship of samples. To overcome this limitation, KDSR first maps the sample into high‐dimensional feature space via kernel tricks and then performs the discriminative sparse representation scheme in high‐dimensional feature space. KDSR can capture the non‐linear relationship of samples and contains more discriminative information of samples, which makes it have good classification performance. In addition, KDSR has a closed‐form solution, which makes it computationally efficient and easy to apply in practice. Experimental results on three benchmark databases demonstrate that KDSR can achieve better recognition performance than many state‐of‐the‐art methods.