Name
Title | ||
|---|---|---|
A distance weighted linear regression classifier based on optimized distance calculating approach for face recognition. |
Abstract | ||
|---|---|---|
Linear regression technique is an efficient method to solve face recognition problem. It’s based on the theory that images in the same class will also belong to same linear subspace and they can be represented through a linear equation. However, this method suffers from some misclassification problems for the infinite ductility of regression equation, moreover, it also doesn’t make a proper and full use of the information in each sample. For overcoming these problems, a novel algorithm named the Distance Weighted Regression Classifier (DWLRC) is proposed here. It can be used for face recognition under different expression and illumination conditions through a distance weighted method, and it can also be used for optimizing the error in the final distance calculating stage. Experiments on three benchmarks show the better performance of our DWLRC compared with the traditional LRC and some state-of-art methods. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1007/s11042-019-07943-0 | Multimedia Tools and Applications |
Keywords | Field | DocType |
Face recognition, Linear regression, Nearest subspace classifier, Object recognition | Facial recognition system,Linear equation,Pattern recognition,Regression analysis,Computer science,Unit-weighted regression,Linear subspace,Artificial intelligence,Classifier (linguistics),Linear regression,Cognitive neuroscience of visual object recognition | Journal |
Volume | Issue | ISSN |
78 | 22 | 1380-7501 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tang Lin-Lin | 1 | 31 | 12.25 |
| Huifen Lu | 2 | 0 | 0.68 |
| Zhen Pang | 3 | 0 | 0.68 |
| Zhangyan Li | 4 | 0 | 0.68 |
| Jing-yong Su | 5 | 156 | 10.93 |