Collaborative representation based projections for face recognition

Abstract

In this paper, we develop a collaborative representation based projections (CRP) for face recognition, which is an unsupervised method. Like SPP and NPE, CRP aims to preserve the sparse reconstruction relations of data. CRP is much faster than SPP since CRP adopts collaborative representation with regularized least square related as objective function while SPP adopts sparse representation related as objective function. Experimental results on ORL and FERET demonstrate that CRP works well in feature extraction and leads to good recognition performance. © 2012 Springer-Verlag.