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Highlights from
Active Shape Model (ASM) and Active Appearance Model (AAM)

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from Active Shape Model (ASM) and Active Appearance Model (AAM) by Dirk-Jan Kroon
Cootes 2D/3D Active Shape & Appearance Model for automatic image object segmentation and recognition

[Evalues, Evectors, x_mean]=PCA(x) 
function [Evalues, Evectors, x_mean]=PCA(x)
% PCA using Single Value Decomposition
% Obtaining mean vector, eigenvectors and eigenvalues
%
% [Evalues, Evectors, x_mean]=PCA(x);
%
% inputs,
%   X : M x N matrix with M the trainingvector length and N the number
%              of training data sets
%
% outputs,
%   Evalues : The eigen values of the data
%   Evector : The eigen vectors of the data
%   x_mean : The mean training vector
%
%
s=size(x,2);
% Calculate the mean 
x_mean=sum(x,2)/s;

% Substract the mean
x2=(x-repmat(x_mean,1,s))/ sqrt(s-1);

% Do the SVD 
%[U2,S2] = svds(x2,s); 
[U2,S2] = svd(x2,0);

Evalues=diag(S2).^2;
Evectors=bsxfun(@times,U2,sign(U2(1,:)));

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