Name
Abstract | ||
|---|---|---|
In this paper, we propose a fast and robust face recognition method named enhancing sparsity via full rank decomposition. The proposed method first represents the test sample as a linear combination of the training data as the same as sparse representation, then make a full rank decomposition of the training data matrix. We obtain the generalized inverse of the training data matrix and then solve the general solution of the linear equation directly. For obtaining the optimum solution to represent the test sample, we use the least square method to solve it. We classify the test sample into the class which has the minimal reconstruction error. Our method can solve the optimum solution of the linear equation, and it is more suitable for face recognition than sparse representation classifier. The extensive experimental results on publicly available face databases demonstrate the effectiveness of the proposed method for face recognition. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/s00521-014-1582-4 | Neural Computing and Applications |
Keywords | DocType | Volume |
DISCRIMINANT-ANALYSIS,REPRESENTATION,MINIMIZATION | Journal | 25 |
Issue | ISSN | Citations |
5 | 1433-3058 | 2 |
PageRank | References | Authors |
0.39 | 23 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuwu Lu | 1 | 196 | 12.50 |
| Jinrong Cui | 2 | 54 | 4.67 |
| Xiaozhao Fang | 3 | 102 | 11.44 |