Name
Title | ||
|---|---|---|
Two-dimensional direct discriminant locality preserving projection analysis for face recognition |
Abstract | ||
|---|---|---|
To make use of information contained in the null space of withinclass during the implementation of discriminant locality preserving projection(DLPP), a very efficient feature extraction algorithm called two-dimensional direct discriminant LPP (2D-DDLPP) algorithm is proposed for face recognition in this paper. By modifying the simultaneous diagonalization procedure, the null space of the interclass matrix can be discarded for it carries no discriminative information and the null space of intraclass matrix is preserved for it contains very important information for classification. Also, the 2D-DDLPP algorithm does not need to transform 2D image matrix into a vector prior to feature extraction so that it can be implemented more efficient and accurate than the 1D traditional in extracting the facial features. Therefore, the performance of 2D-DDLPP has been greatly improved. Extensive experiments are performed to test and evaluate the new algorithm using the UMIST and the AR face databases. The experimental results indicate that our proposed 2D DDLPP method is not only computationally more efficiently but also more accurate than the 2DLPP method in extracting the facial features for face recognition. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/ISBAST.2014.7013087 | ISBAST |
Keywords | Field | DocType |
face recognition,feature extraction,simultaneous diagonalization procedure,interclass matrix,matrix algebra,direct discriminant nalysis,2d image matrix,image classification,feature extraction algorithm,dlpp,two-dimensional locality preserving projection,two-dimensional direct discriminant locality preserving projection analysis | Kernel (linear algebra),k-nearest neighbors algorithm,Facial recognition system,Computer vision,Locality,Pattern recognition,Discriminant,Matrix (mathematics),Computer science,Feature extraction,Artificial intelligence,Discriminative model | Conference |
Citations | PageRank | References |
0 | 0.34 | 11 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hengjian Li | 1 | 4 | 3.10 |
| Jinwen Dong | 2 | 0 | 0.34 |
| Jinping Li | 3 | 0 | 0.34 |