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We develop a face recognition algorithm which is insensitive to large variation in lighting direction and facial expression.
Taking a pattern classification approach, we consider each pixel in an image as a coordinate in a high-dimensional space. We take
advantage of the observation that the images of a particular face, under varying illumination but fixed pose, lie in a 3D linear
subspace of the high dimensional image space—if the face is a Lambertian surface without shadowing. However, since faces are
not truly Lambertian surfaces and do indeed produce self-shadowing, images will deviate from this linear subspace. Rather than
explicitly modeling this deviation, we linearly project the image into a subspace in a manner which discounts those regions of the
face with large deviation. Our projection method is based on Fisher’s Linear Discriminant and produces well separated classes in a
low-dimensional subspace, even under severe variation in lighting and facial expressions. The Eigenface technique, another method
based on linearly projecting the image space to a low dimensional subspace, has similar computational requirements. Yet, extensive
experimental results demonstrate that the proposed “Fisherface” method has error rates that are lower than those of the Eigenface
technique for tests on the Harvard and Yale Face Databases. A complete list of public face databases is available at
http://www.advancedsourcecode.com/facedatabase.asp.
Index terms: appearance-based vision, face recognition, illumination
invariance, Fisher’s linear discriminant, face recognition, face
matching, face identification, PCA, principal components analysis, fisherfaces.
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Figure 1. Eigenfaces of faces from the ORL face database. |
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A simple and effective source code for Face Recognition Based on FisherFaces. All tests were performed on AT&T database. |
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Demo code (protected
P-files) available for performance evaluation. Matlab
Image Processing Toolbox is required. |
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Release |
Date |
Major features |
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1.0 |
2006.01.17 |
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We recommend to check the secure connection to PayPal, in order to avoid any fraud. This donation has to be considered an encouragement to improve the code itself. |
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Face Recognition Based on FisherFaces - Release 1.0 - Click here for
your donation. In order to obtain the source code you
have to pay a little sum of money: 49 EUROS (less than
68,6 U.S. Dollars). |
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Once you have done this, please email us luigi.rosa@tiscali.it As soon as possible (in a few days) you will receive our new release of Face Recognition Based on FisherFaces. Alternatively, you can bestow using our banking coordinates:
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The authors have no relationship or partnership
with The Mathworks. All the code provided is written in Matlab
language (M-files and/or M-functions), with no dll or other
protected parts of code (P-files or executables). The code was
developed with Matlab 14 SP1. Matlab Image Processing Toolbox is required.
The code provided has to be considered "as is" and it is without any kind of warranty. The
authors deny any kind of warranty concerning the code as well
as any kind of responsibility for problems and damages which may
be caused by the use of the code itself including all parts of
the source code.
