Name
Abstract | ||
|---|---|---|
In this paper, we propose a face recognition method using a fusion method based on bidirectional 2DPCA. While the previous PCA method computes the covariance matrix by using a one-dimensional vector, 2DPCA method computes the covariance matrix by directly using a direct two-dimensional image, and extracts the feature vectors by solving an eigenvalue problem. The proposed method recognizes the faces by applying the modified 2DPCA obtaining a linear transformation matrix using two covariance matrices which are the row and column covariance matrices. The experimental results indicate that the proposed method shows a higher and more stable recognition rate than the conventional methods. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1016/j.amc.2008.05.032 | Applied Mathematics and Computation |
Keywords | Field | DocType |
Face recognition,Two-dimensional PCA,Fusion method | Facial recognition system,Feature vector,Matrix (mathematics),Algorithm,Covariance intersection,Matrix method,Covariance matrix,Mathematics,Eigenvalues and eigenvectors,Covariance | Journal |
Volume | Issue | ISSN |
205 | 2 | 0096-3003 |
Citations | PageRank | References |
14 | 0.89 | 13 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Young-Gil Kim | 1 | 26 | 5.90 |
| Young-Jun Song | 2 | 25 | 3.80 |
| Un-dong Chang | 3 | 22 | 2.42 |
| Dong-Woo Kim | 4 | 14 | 1.90 |
| Tae-Sung Yun | 5 | 14 | 1.22 |
| Jae-Hyeong Ahn | 6 | 16 | 2.95 |