eigenfaces algorithm

project faces to eigen faces for face detection
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Updated 17 Mar 2014

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given set of facesthe object is face recognition. we project the faces to new fielad of eigen faces which are actualy eigen vectors the same as PCA algorithm
THANKS TO THE SITE http://fewtutorials.bravesites.com/tutorials
steps
1) resize all M faces to N*N
2) remove average
3) create matrix A of faces each row N*N
totla size of A is (N*N) * M
4) calculate average face
5) remove average face from A
6) compute the covariance matrix C A'*A , C size is M*M
7) compute eigen values and eigen vectors , to compute the eigne faces need to go bacj to higher dimension
8) compute the linear combination of each original face
9( given new face project it to eigen face and compute distance to each eigen face this is the recognition.

Cite As

michael scheinfeild (2024). eigenfaces algorithm (https://www.mathworks.com/matlabcentral/fileexchange/45915-eigenfaces-algorithm), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2009a
Compatible with any release
Platform Compatibility
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Version Published Release Notes
1.0.0.0