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    <p>What etarion said is correct. </p> <p>To copy a column or row you always have to write:</p> <pre><code>Mat B = mat.col(i); A.copyTo(B); </code></pre> <p>The following program shows how to perform a PCA in OpenCV. It'll show the mean image and the first three Eigenfaces. The images I used in there are available from <a href="http://www.cl.cam.ac.uk/research/dtg/attarchive/facedatabase.html">http://www.cl.cam.ac.uk/research/dtg/attarchive/facedatabase.html</a>:</p> <pre><code>#include "cv.h" #include "highgui.h" using namespace std; using namespace cv; Mat normalize(const Mat&amp; src) { Mat srcnorm; normalize(src, srcnorm, 0, 255, NORM_MINMAX, CV_8UC1); return srcnorm; } int main(int argc, char *argv[]) { vector&lt;Mat&gt; db; // load greyscale images (these are from http://www.cl.cam.ac.uk/research/dtg/attarchive/facedatabase.html) db.push_back(imread("s1/1.pgm",0)); db.push_back(imread("s1/2.pgm",0)); db.push_back(imread("s1/3.pgm",0)); db.push_back(imread("s2/1.pgm",0)); db.push_back(imread("s2/2.pgm",0)); db.push_back(imread("s2/3.pgm",0)); db.push_back(imread("s3/1.pgm",0)); db.push_back(imread("s3/2.pgm",0)); db.push_back(imread("s3/3.pgm",0)); db.push_back(imread("s4/1.pgm",0)); db.push_back(imread("s4/2.pgm",0)); db.push_back(imread("s4/3.pgm",0)); int total = db[0].rows * db[0].cols; // build matrix (column) Mat mat(total, db.size(), CV_32FC1); for(int i = 0; i &lt; db.size(); i++) { Mat X = mat.col(i); db[i].reshape(1, total).col(0).convertTo(X, CV_32FC1, 1/255.); } // Change to the number of principal components you want: int numPrincipalComponents = 12; // Do the PCA: PCA pca(mat, Mat(), CV_PCA_DATA_AS_COL, numPrincipalComponents); // Create the Windows: namedWindow("avg", 1); namedWindow("pc1", 1); namedWindow("pc2", 1); namedWindow("pc3", 1); // Mean face: imshow("avg", pca.mean.reshape(1, db[0].rows)); // First three eigenfaces: imshow("pc1", normalize(pca.eigenvectors.row(0)).reshape(1, db[0].rows)); imshow("pc2", normalize(pca.eigenvectors.row(1)).reshape(1, db[0].rows)); imshow("pc3", normalize(pca.eigenvectors.row(2)).reshape(1, db[0].rows)); // Show the windows: waitKey(0); } </code></pre> <p>and if you want to build the matrix by row (like in your original question above) use this instead:</p> <pre><code>// build matrix Mat mat(db.size(), total, CV_32FC1); for(int i = 0; i &lt; db.size(); i++) { Mat X = mat.row(i); db[i].reshape(1, 1).row(0).convertTo(X, CV_32FC1, 1/255.); } </code></pre> <p>and set the flag in the PCA to:</p> <pre><code>CV_PCA_DATA_AS_ROW </code></pre> <p>Regarding machine learning. I wrote a document on machine learning with the OpenCV C++ API that has examples for most of the classifiers, including Support Vector Machines. Maybe you can get some inspiration there: <a href="http://www.bytefish.de/pdf/machinelearning.pdf">http://www.bytefish.de/pdf/machinelearning.pdf</a>.</p>
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