Abstract
In this paper we propose a two-dimensional (2D) Laplacianfaces method for face recognition. The new algorithm is developed based on two techniques, i.e., locality preserved embedding and image based projection. The 2D Laplacianfaces method is not only computationally more efficient but also more accurate than the one-dimensional (1D) Laplacianfaces method in extracting the facial features for human face authentication. Extensive experiments are performed to test and evaluate the new algorithm using the FERET and the AR face databases. The experimental results indicate that the 2D Laplacianfaces method significantly outperforms the existing 2D Eigenfaces, the 2D Fisherfaces and the 1D Laplacianfaces methods under various experimental conditions.
Original language | English |
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Pages (from-to) | 3237-3243 |
Number of pages | 7 |
Journal | Pattern Recognition |
Volume | 41 |
Issue number | 10 |
DOIs | |
Publication status | Published - 1 Oct 2008 |
Keywords
- Eigenfaces
- Feature extraction
- Fisherfaces
- Image based projection
- Two-dimensional Laplacianfaces
ASJC Scopus subject areas
- Computer Vision and Pattern Recognition
- Signal Processing
- Electrical and Electronic Engineering