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我正在尝试在 Matlab 中实现一个非常基本的特征脸计算。它有点工作，但我只得到两个有意义的特征值——其余的都是零。相应的特征向量似乎是正确的，因为它们中的大多数在转换为图像时都会显示特征面。

那么为什么我的大多数特征值都为零？我需要它们不同于零，以便按其重要性（最大特征值）对特征面进行排序。

我正在阅读 400 张图片，每个尺寸 h/w = 112/92 px 它们可以在这里找到：http: //www.cl.cam.ac.uk/Research/DTG/attarchive/pub/data/att_faces.zip

编码：

clear all;

files = dir('eigenfaces2/training/*.pgm');
[numFaces, discard] = size(files);

h = 112;
w = 92;
s = h * w;

%calculate average face
avgFace = zeros(s, 1);
faces = [];
for i=1:numFaces
  file = strcat('eigenfaces2/training/', files(i).name);
  im = double(imread(file));
  im = reshape(im, s, 1);
  avgFace = avgFace + im;
  faces(:,i) = im;
end
avgFace = avgFace ./ numFaces;

A = [];
for i=1:numFaces
  diff = avgFace - faces(i);
  A(:,i) = diff;
end

numEigs = 20;

L = (A' * A) / numFaces; 
[tmpEigs, discard] = eigs(L, numEigs);
eigenfaces = [];
for i=1:numEigs
  v = tmpEigs(:,i);
  eigenfaces(:,i) = A * v;
end

%visualize largest eigenfaces
figure;
for i=1:numEigs
  eigface = eigenfaces(:,i);
  mmax = max(eigface);
  mmin = min(eigface);
  eigface = 255 .* (eigface-mmin) ./ (mmax-mmin);
  eigface = reshape(eigface, h, w);
  subplot(4,5,i); imshow(uint8(eigface));
end
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1 回答 1

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I've don't have much experience with computer vision/image recognition, but I think you might want

diff = avgFace - faces(:,i);

in your second for loop. Otherwise it's just subtracting a constant from avgFace each time, and so A (and hence L) only gets a rank of 2.

于 2012-02-17T18:47:00.057 回答