//Ax+by+cz=D
void cvFitPlane(const CvMat* points, float* plane){
// Estimate geometric centroid.
int nrows = points->rows;
int ncols = points->cols;
int type = points->type;
CvMat* centroid = cvCreateMat(1, ncols, type);
cvSet(centroid, cvScalar(0));
for (int c = 0; c<ncols; c++){
for (int r = 0; r < nrows; r++)
{
centroid->data.fl[c] += points->data.fl[ncols*r + c];
}
centroid->data.fl[c] /= nrows;
}
// Subtract geometric centroid from each point.
CvMat* points2 = cvCreateMat(nrows, ncols, type);
for (int r = 0; r<nrows; r++)
for (int c = 0; c<ncols; c++)
points2->data.fl[ncols*r + c] = points->data.fl[ncols*r + c] - centroid->data.fl[c];
// Evaluate SVD of covariance matrix.
CvMat* A = cvCreateMat(ncols, ncols, type);
CvMat* W = cvCreateMat(ncols, ncols, type);
CvMat* V = cvCreateMat(ncols, ncols, type);
cvGEMM(points2, points, 1, NULL, 0, A, CV_GEMM_A_T);
cvSVD(A, W, NULL, V, CV_SVD_V_T);
// Assign plane coefficients by singular vector corresponding to smallest singular value.
plane[ncols] = 0;
for (int c = 0; c<ncols; c++){
plane[c] = V->data.fl[ncols*(ncols - 1) + c];
plane[ncols] += plane[c] * centroid->data.fl[c];
}
// Release allocated resources.
cvReleaseMat(¢roid);
cvReleaseMat(&points2);
cvReleaseMat(&A);
cvReleaseMat(&W);
cvReleaseMat(&V);
}
调用的方式:[cpp] view plain copy
CvMat*points_mat = cvCreateMat(X_vector.size(), 3, CV_32FC1);//定义用来存储需要拟合点的矩阵
for (int i=0;i < X_vector.size(); ++i)
{
points_mat->data.fl[i*3+0] = X_vector[i];//矩阵的值进行初始化 X的坐标值
points_mat->data.fl[i * 3 + 1] = Y_vector[i];// Y的坐标值
points_mat->data.fl[i * 3 + 2] = Z_vector[i];<span style="font-family: Arial, Helvetica, sans-serif;">// Z的坐标值</span>
}
float plane12[4] = { 0 };//定义用来储存平面参数的数组
cvFitPlane(points_mat, plane12);//调用方程 我们拟合出来的方程:Ax+By+Cz=D其中 A=plane12[0], B=plane12[1], C=plane12[2], D=plane12[3],在网上看到这个拟合平面的程序,不是很懂X_vector.size(),X_vector[i],Y_vector[i],Z_vector[i]这三个参数的含义,是要把x,y,z的坐标分别放进那三个矩阵中吗?那data.fl[]又是什么意思?求大神解答要是有别的实现算法也万分感谢
void cvFitPlane(const CvMat* points, float* plane){
// Estimate geometric centroid.
int nrows = points->rows;
int ncols = points->cols;
int type = points->type;
CvMat* centroid = cvCreateMat(1, ncols, type);
cvSet(centroid, cvScalar(0));
for (int c = 0; c<ncols; c++){
for (int r = 0; r < nrows; r++)
{
centroid->data.fl[c] += points->data.fl[ncols*r + c];
}
centroid->data.fl[c] /= nrows;
}
// Subtract geometric centroid from each point.
CvMat* points2 = cvCreateMat(nrows, ncols, type);
for (int r = 0; r<nrows; r++)
for (int c = 0; c<ncols; c++)
points2->data.fl[ncols*r + c] = points->data.fl[ncols*r + c] - centroid->data.fl[c];
// Evaluate SVD of covariance matrix.
CvMat* A = cvCreateMat(ncols, ncols, type);
CvMat* W = cvCreateMat(ncols, ncols, type);
CvMat* V = cvCreateMat(ncols, ncols, type);
cvGEMM(points2, points, 1, NULL, 0, A, CV_GEMM_A_T);
cvSVD(A, W, NULL, V, CV_SVD_V_T);
// Assign plane coefficients by singular vector corresponding to smallest singular value.
plane[ncols] = 0;
for (int c = 0; c<ncols; c++){
plane[c] = V->data.fl[ncols*(ncols - 1) + c];
plane[ncols] += plane[c] * centroid->data.fl[c];
}
// Release allocated resources.
cvReleaseMat(¢roid);
cvReleaseMat(&points2);
cvReleaseMat(&A);
cvReleaseMat(&W);
cvReleaseMat(&V);
}
调用的方式:[cpp] view plain copy
CvMat*points_mat = cvCreateMat(X_vector.size(), 3, CV_32FC1);//定义用来存储需要拟合点的矩阵
for (int i=0;i < X_vector.size(); ++i)
{
points_mat->data.fl[i*3+0] = X_vector[i];//矩阵的值进行初始化 X的坐标值
points_mat->data.fl[i * 3 + 1] = Y_vector[i];// Y的坐标值
points_mat->data.fl[i * 3 + 2] = Z_vector[i];<span style="font-family: Arial, Helvetica, sans-serif;">// Z的坐标值</span>
}
float plane12[4] = { 0 };//定义用来储存平面参数的数组
cvFitPlane(points_mat, plane12);//调用方程 我们拟合出来的方程:Ax+By+Cz=D其中 A=plane12[0], B=plane12[1], C=plane12[2], D=plane12[3],在网上看到这个拟合平面的程序,不是很懂X_vector.size(),X_vector[i],Y_vector[i],Z_vector[i]这三个参数的含义,是要把x,y,z的坐标分别放进那三个矩阵中吗?那data.fl[]又是什么意思?求大神解答要是有别的实现算法也万分感谢
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