Name
Abstract | ||
|---|---|---|
This paper presents a new scheme of face image feature extraction, namely, the two-dimensional Fisher linear discriminant. Experiments on the ORL and the UMIST face databases show that the new scheme outperforms the PCA and the conventional PCA+FLD schemes, not only in its computational efficiency, but also in its performance for the task of face recognition. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1016/j.patcog.2004.12.003 | Pattern Recognition |
Keywords | Field | DocType |
Fisher criterion,Principal component analysis (PCA),Linear discriminant analysis (LDA) | Facial recognition system,Pattern recognition,Kernel Fisher discriminant analysis,Feature extraction,Speech recognition,Artificial intelligence,Linear discriminant analysis,Fisher criterion,Mathematics,Machine learning | Journal |
Volume | Issue | ISSN |
38 | 7 | 0031-3203 |
Citations | PageRank | References |
70 | 2.56 | 2 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Huilin Xiong | 1 | 358 | 21.58 |
| M. N. Swamy | 2 | 104 | 18.85 |
| M.O. Ahmad | 3 | 72 | 3.17 |