FLD-based Face Recognition System

This package implements 'Fisherface', a FLD-based face recognition system.

Description

This package implements a well-known FLD-based face recognition method, which is called 'Fisherface'.
All functions are easy to use, as they are heavy commented. Furthermore, a sample script and two small training and test databases are included to show their usage.

• Required Products: Image Processing Toolbox
• MATLAB release: MATLAB 7.2 (R2006a)

[kaveh Rad]

Thank you for your Excellent and clearly Code

[radha lak]

good

[Syed Adnan Ahmed]

Thanks for your code
they are commented to the max level
keep up the good work

[Dilip kumar]

thanks a lot

[Chao Wang]

perfect except that there are two little problems in matlab 6.5

[chao shi]

Thank you very much for your code.

[Angshul Majumdar]

Works well for the toy example provided. Should have been more general.

[Amir Omidvarnia]

Dear friend! My code is only a prototype of FLD-based face recognition systems. In fact, this code implements the core algorithm for the system. So, you shouldn't expect it to work well on all datasets. Instead, you can customize it according to your needs and used facial images.

[Sergio Rodriguez]

It simply works

[Kahn615 Y]

Thanks

[Mike Gu]

Thanks.

BTW, can I ask why in FisherfaceCore.m - under "Sorting and eliminating small eigenvalues" we don't need to fliplr "V" first since eigenvalues there are in ascending order? is it mean we eliminate large eigenvalues?

[Tsai zhenhua]

 

[Tsai zhenhua]

Inthe Sb part, there should be a multipler 2, right?

[Tsai zhenhua]

And the PCA, the eigen vectors selected should be corresponding to the largest eigen values but in the source code it is opposite,
my email is: [e-mail]
expect to dicuss with u:)

[Mr Smart]

 

[Jaime]

Tsai there is a mistake indeed; the order of the eigenvectors is backwars, and you are using the eigenvectors with less relevance.

In line 43 of FisherfaceCore.m, you have to substitute line 43:

"for i = 1 : P-Class_number"

for

"for i = P:-1:Class_number+1"

This will solve the problem. I tested with all the faces in the sample set, and it was 90% accurate.

Everything has been working perfectly, thanks for an excellent and well commented code Amir!

[Jaime]

 

[Jaime]

Tsai, I forgot to mention that Sb should be multiplied by the number of pcitures per class (in this case 2), you are right on that too. Refer to section 2.4 of the following paper to note the error: http://www.face-rec.org/algorithms/LDA/belhumeur96eigenfaces.pdf

If you guys would like to look at another sample Matlab code for fisher faces, look at:

http://dailyburrito.com/projects/facerecog/FaceRecReport.html