Project: Eigenfaces and Fisherfaces
Table of Contents |
Developer | sonots |
---|---|
First Edition | 05/2006 |
Last Modified | 10/2007 |
Language | Matlab |
Abstract
This project describes a study of two traditional face recognition methods, the Eigenface [10] and the Fisherface [7]. The Eigenface is the first method considered as a successful technique of face recognition. The Eigenface method uses Principal Component Analysis (PCA) to linearly project the image space to a low dimensional feature space. The Fisherface method is an enhancement of the Eigenface method that it uses Fisher’s Linear Discriminant Analysis (FLDA or LDA) for the dimensionality reduction. The LDA maximizes the ratio of between-class scatter to that of within-class scatter, therefore, it works better than PCA for purpose of discrimination. The Fisherface is especially useful when facial images have large variations in illumination and facial expression. In this project, a comparison of the Eigenface and the Fisherface methods respect to facial images having large illumination variations is examined.
The report is available at EigenFisherFace.pdf
Tag: Scientific ComputerVision Face Recognition Matlab
Source Codes
- cvpr:cvPca.m
- cvpr:cvPcaProj.m
- cvpr:cvPcaInvProj.m
- cvpr:cvLda.m
- cvpr:cvLdaProj.m
- cvpr:cvLdaInvProj.m
- cvpr:cvKnn.m
- cvpr:project/EigenFisherFace/Eigenface.m
- cvpr:project/EigenFisherFace/Fisherface.m
Experimental Project Codes and Data. Download
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References
- [1] G. Shakhnarovich, B. Moghaddam, Face Recognition in Subspaces, Handbook of Face Recognition, Eds. Stan Z. Li and Anil K. Jain, Springer-Verlag, December 2004, p142-144 http://www.face-rec.org/interesting-papers/General/TR2004-041.pdf
Amazon.com Amazon.co.jp
- [2] M. Turk, Eigen Faces and Beyond, Face Processing: Advanced Modeling and Methods, Eds. Wenyi Zhao, Rama Chellappa, Academic Press, February 2006, Section 2.3.
Amazon.com
Amazon.co.jp
- [3] Karhunen-Loeve Transform by Kristina Scherbaum
- [4] F. Samaria and A. Harter "Parameterisation of a stochastic model for human face identification" 2nd IEEE Workshop on Applications of Computer Vision December 1994, Sarasota (Florida). http://www.cl.cam.ac.uk/Research/DTG/publications/public/files/paper.95.2.ps.Z
(Database is available at http://www.cl.cam.ac.uk/Research/DTG/attarchive/facedatabase.html
and it is free.)