急求基于pca人脸识别matlab程序的一些指导

function pca (path, trainList, subDim)
if nargin < 3
    subDim = dim - 1;
end;


disp(' ')

load listAll;

% Constants
numIm = 3816;


% Memory allocation for DATA matrix
fprintf('Creating DATA matrix\n')
tmp = imread ( [path char(listAll(1)) '.pgm'] );
[m, n] = size (tmp);                    % image size - used later also!!!
DATA = uint8 (zeros(m*n, numIm));       % Memory allocated
clear str tmp;

% Creating DATA matrix
for i = 1 : numIm
    im = imread ( [path char(listAll(i)) '.pgm'] );
    DATA(:, i) = reshape (im, m*n, 1);
end;
save DATA DATA;
clear im;

% Creating training images space
fprintf('Creating training images space\n')
dim = length (trainList);
imSpace = zeros (m*n, dim);
for i = 1 : dim
    index = strmatch (trainList(i), listAll);
    imSpace(:, i) = DATA(:, index);
end;
save imSpace imSpace;
clear DATA;

% Calculating mean face from training images
fprintf('Zero mean\n')
psi = mean(double(imSpace'))';
save psi psi;

% Zero mean
zeroMeanSpace = zeros(size(imSpace));
for i = 1 : dim
    zeroMeanSpace(:, i) = double(imSpace(:, i)) - psi;
end;
save zeroMeanSpace zeroMeanSpace;
clear imSpace;

% PCA
fprintf('PCA\n')
L = zeroMeanSpace' * zeroMeanSpace;         % Turk-Pentland trick (part 1)
[eigVecs, eigVals] = eig(L);

diagonal = diag(eigVals);
[diagonal, index] = sort(diagonal);
index = flipud(index);
 
pcaEigVals = zeros(size(eigVals));
for i = 1 : size(eigVals, 1)
    pcaEigVals(i, i) = eigVals(index(i), index(i));
    pcaEigVecs(:, i) = eigVecs(:, index(i));
end;

pcaEigVals = diag(pcaEigVals);
pcaEigVals = pcaEigVals / (dim-1);
pcaEigVals = pcaEigVals(1 : subDim);        % Retaining only the largest subDim ones

pcaEigVecs = zeroMeanSpace * pcaEigVecs;    % Turk-Pentland trick (part 2)

save pcaEigVals pcaEigVals;

% Normalisation to unit length
fprintf('Normalising\n')
for i = 1 : dim
    pcaEigVecs(:, i) = pcaEigVecs(:, i) / norm(pcaEigVecs(:, i));
end;

% Dimensionality reduction. 
fprintf('Creating lower dimensional subspace\n')
w = pcaEigVecs(:, 1:subDim);
save w w;
clear w;

% Subtract mean face from all images
load DATA;
load psi;
zeroMeanDATA = zeros(size(DATA));
for i = 1 : size(DATA, 2)
    zeroMeanDATA(:, i) = double(DATA(:, i)) - psi;
end;
clear psi;
clear DATA;

% Project all images onto a new lower dimensional subspace (w)
fprintf('Projecting all images onto a new lower dimensional subspace\n')
load w;
pcaProj = w' * zeroMeanDATA;
clear w;
clear zeroMeanDATA;
save pcaProj pcaProj; 
这个程序运行时总有毛病，希望大神们帮忙指导一下。我QQ214883996

答案：你的路径还有训练图片,测试图片都没有定义啊,肯定不能运行啊.

其他：princomp你可以看下这个函数，matlab提供的pca函数~
而且你也可以查下K-L变换和svd,希望对你有帮助吧，程序是看不太明白。 

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