Name
Abstract | ||
|---|---|---|
A dynamically optimizing PCA method for face recognition is presented. Firstly, DCT is adopted, and their mean gray values are obtained. The face images are grouped into three sorted groups: Large, Medium and Small, and then calculate their means. Then, the Eigenvalue number is chosen as 9 and 10. Finally, recognition and reconstruction may be accomplished. The results show that this method achieved better results compared to a number of state of the art PCA variants. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/ICCAIS.2015.7338646 | 2015 International Conference on Control, Automation and Information Sciences (ICCAIS) |
Keywords | Field | DocType |
face recognition,principle component analysis,Eigenvalue | Frequency domain,Facial recognition system,Eigenface,Pattern recognition,Discrete cosine transform,Artificial intelligence,Discrete cosine transforms,Principal component analysis,Mathematics,Eigenvalues and eigenvectors | Conference |
ISSN | Citations | PageRank |
2475-7896 | 0 | 0.34 |
References | Authors | |
9 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhihong Zhao | 1 | 0 | 0.34 |
| Beibei Li | 2 | 2 | 0.73 |