Name
Abstract | ||
|---|---|---|
Sparse representation has attracted great attention in past years. Sparse Representation-based Classification (SRC) algorithm was developed and successfully used in face recognition. However, the importance of sparsity is much emphasized in SRC and the use of collaborative representation (CR) in SRC is ignored. In reality, it is the collaborative representation but not the l1-norm sparsity that makes SRC powerful for face recogntion. Based on collaborative representation based classification (CRC) method, we proposed an enhanced collaborative representation based classification (ECRC). Experimental results on face databases demonstrate the effectiveness of our method. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/ICInfA.2014.6932697 | Information and Automation |
Keywords | Field | DocType |
face recognition,image classification,image enhancement,image representation,linear programming,sparse matrices,ecrc method,src algorithm,enhanced collaborative representation based classification method,face databases,l1-norm sparsity,sparse representation-based classification algorithm,sparse representation,collaborative representation,enhanced collaborative representation based classification (ecrc),face,classification algorithms,databases,collaboration | Facial recognition system,Computer science,Sparse approximation,Artificial intelligence,Statistical classification,Machine learning | Conference |
Citations | PageRank | References |
0 | 0.34 | 11 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhonghua Liu | 1 | 115 | 11.12 |
| Xu-Hui Zhao | 2 | 4 | 1.79 |
| Tao Huang | 3 | 15 | 0.88 |
| Jiexin Pu | 4 | 92 | 19.85 |
| yanna si | 5 | 1 | 2.04 |