ayy

function [Match] = recognise(UnknownFace,Crop)
% 2 reshape to vectors and append to matrix
for i=1:size(Crop,3),
    X(:,i)=reshape(Crop(:,:,i),[10000 1]);
end

% 3 calculate average face

averageFace=mean(X')';

% 4 mean subtract average face
A=double(X)-repmat(averageFace,[1 size(X,2)]);

% 5 compute Eigenfaces
EigNumber=20; % try different numbers of dimensions
% [U,S,V]=svd(A);
[U,S,V]=svds(A,EigNumber);

% 6 project all known faces to low dimensional face space
LTFaces=(U(:,1:EigNumber)')*(double(X)-repmat(averageFace,[1  size(X,2)]));

% 7 recognise unknown face

% project to low dimensions
LUnknownFace=U(:,1:EigNumber)'*(double(reshape(UnknownFace,[10000 1]))-averageFace);

% calculate distances to known faces
EuclideanDist=sqrt(sum((LTFaces-repmat(LUnknownFace,[1 size(Crop,3)])).^2));

% find closest matching known face
[match_score, match]=min(EuclideanDist);

% display known face
imagesc(reshape(X(:,match),[100 100]));
Match = reshape(X(:,match),[100 100]);

end