PCA小测试 

 1 #include <iostream>
 2 #include "opencv2/opencv.hpp"
 3 const int ROW = 2;
 4 const int COL = 5;
 5 //PCA
 6 int main()
 7 {
 8     float m_matrix[ROW][COL] = { { -1, -1, 0, 2, 0 }, {-2, 0, 0, 1, 1} },mROWmean[ROW][1];
 9     float m_sum=0;
10     cv::Mat eigenvalues, eigenvectors, k_matrix,pca_matrix;
11     cv::Mat mMatrix(cv::Size(COL,ROW),CV_32FC1,m_matrix);
12     std::cout << mMatrix << std::endl;//原始矩阵
13     for (int i = 0; i < ROW; i++)
14     {
15         for (int j = 0; j < COL; j++)
16         {
17             m_sum += mMatrix.at<float>(i, j);
18         }
19         mROWmean[i][1] = m_sum/COL;
20         m_sum = 0;
21         for (int k = 0; k < COL; k++)
22         {
23             mMatrix.at<float>(i,k) -= mROWmean[i][1];
24         }
25     }
26     //std::cout << mMatrix << std::endl;//减去行均值后的矩阵
27     cv::Mat covar = (mMatrix*mMatrix.t()) / (mMatrix.cols);//计算协方差
28     //std::cout << covar << std::endl;
29     cv::eigen(covar,eigenvalues,eigenvectors);//计算特征向量和特征值
30     //std::cout << eigenvectors << std::endl;
31     /*for (int i = 0; i < eigenvectors.cols; i++)
32     {
33         k_matrix.at<float>(0, i) = eigenvectors.at<float>(0,i);
34     }*/
35     pca_matrix = eigenvectors.row(0)*mMatrix;
36     std::cout << pca_matrix << std::endl;
37     system("pause");
38     return 0;
39 }

 

posted @ 2017-10-31 19:42  CV_JIANG  阅读(298)  评论(0)    收藏  举报