eigenfaces algorithm

project faces to eigen faces for face detection

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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.

Citation pour cette source

michael scheinfeild (2026). eigenfaces algorithm (https://fr.mathworks.com/matlabcentral/fileexchange/45915-eigenfaces-algorithm), MATLAB Central File Exchange. Extrait(e) le .

Informations générales

Compatibilité avec les versions de MATLAB

  • Compatible avec toutes les versions

Plateformes compatibles

  • Windows
  • macOS
  • Linux
Version Publié le Notes de version Action
1.0.0.0