verification1.m

compute pca for face detection by matlab

load eigenvector u ;
load eigenvalue ev ;
load mean mn ;
load projected proj ;
load curves X ;

[vecsize,neig] = size(u)
M = 20;         % number of eigenvector to use for verification
Rho = (1/(neig-M))*sum(ev(M+1:neig));

%test = [34 12 34 56 78 12 13 56 12 89 34 190 24 0 17 367 89 134 567 23 120 56 134 169 90 45 12 14 38]';
test = X(:,1) ;
test = test - mn;

Phi = u(:,1:M);
y = Phi'*test;

eps_sqr = (norm(test)^2) - sum(y.^2);

DIFS = sum((y.^2)./(ev(1:M)'));   % distance in feature space
DFFS = eps_sqr/Rho;        % distance from feature space
dx = DIFS + DFFS ;