Name
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. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/978-3-642-33506-8_35 | PATTERN RECOGNITION |
Keywords | Field | DocType |
collaborative representation,feature extraction,face recognition | Facial recognition system,Computer science,FERET,Sparse approximation,Feature extraction,Artificial intelligence,Machine learning | Conference |
Volume | ISSN | Citations |
321 | 1865-0929 | 2 |
PageRank | References | Authors |
0.37 | 27 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wankou Yang | 1 | 535 | 34.68 |
| Changyin Sun | 2 | 2002 | 157.17 |
| Qingshan Liu | 3 | 1021 | 46.49 |
| Karl Ricanek | 4 | 165 | 18.65 |