static int run8Point( const Mat& _m1, const Mat& _m2, Mat& _fmatrix )
{
Point2d m1c(0,0), m2c(0,0);
double t, scale1 = 0, scale2 = 0;
const Point2f* m1 = _m1.ptr<Point2f>();
const Point2f* m2 = _m2.ptr<Point2f>();
CV_Assert( (_m1.cols == 1 || _m1.rows == 1) && _m1.size() == _m2.size());
int i, count = _m1.checkVector(2);
// compute centers and average distances for each of the two point sets
for( i = 0; i < count; i++ )
{
m1c += Point2d(m1[i]);
m2c += Point2d(m2[i]);
}
// calculate the normalizing transformations for each of the point sets:
// after the transformation each set will have the mass center at the coordinate origin
// and the average distance from the origin will be ~sqrt(2).
t = 1./count;
m1c *= t;
m2c *= t;
for( i = 0; i < count; i++ )
{
scale1 += norm(Point2d(m1[i].x - m1c.x, m1[i].y - m1c.y));
scale2 += norm(Point2d(m2[i].x - m2c.x, m2[i].y - m2c.y));
}
scale1 *= t;
scale2 *= t;
if( scale1 < FLT_EPSILON || scale2 < FLT_EPSILON )
return 0;
scale1 = std::sqrt(2.)/scale1;
scale2 = std::sqrt(2.)/scale2;
Matx<double, 9, 9> A;
// form a linear system Ax=0: for each selected pair of points m1 & m2,
// the row of A(=a) represents the coefficients of equation: (m2, 1)'*F*(m1, 1) = 0
// to save computation time, we compute (At*A) instead of A and then solve (At*A)x=0.
for( i = 0; i < count; i++ )
{
double x1 = (m1[i].x - m1c.x)*scale1;
double y1 = (m1[i].y - m1c.y)*scale1;
double x2 = (m2[i].x - m2c.x)*scale2;
double y2 = (m2[i].y - m2c.y)*scale2;
Vec<double, 9> r( x2*x1, x2*y1, x2, y2*x1, y2*y1, y2, x1, y1, 1 );
A += r*r.t();
}
Vec<double, 9> W;
Matx<double, 9, 9> V;
eigen(A, W, V);
for( i = 0; i < 9; i++ )
{
if( fabs(W[i]) < DBL_EPSILON )
break;
}
if( i < 8 )
return 0;
Matx33d F0( V.val + 9*8 ); // take the last column of v as a solution of Af = 0
// make F0 singular (of rank 2) by decomposing it with SVD,
// zeroing the last diagonal element of W and then composing the matrices back.
Vec3d w;
Matx33d U;
Matx33d Vt;
SVD::compute( F0, w, U, Vt);
w[2] = 0.;
F0 = U*Matx33d::diag(w)*Vt;
// apply the transformation that is inverse
// to what we used to normalize the point coordinates
Matx33d T1( scale1, 0, -scale1*m1c.x, 0, scale1, -scale1*m1c.y, 0, 0, 1 );
Matx33d T2( scale2, 0, -scale2*m2c.x, 0, scale2, -scale2*m2c.y, 0, 0, 1 );
F0 = T2.t()*F0*T1;
// make F(3,3) = 1
if( fabs(F0(2,2)) > FLT_EPSILON )
F0 *= 1./F0(2,2);
Mat(F0).copyTo(_fmatrix);
return 1;
}
转载自：https://github.com/opencv/opencv/blob/3.1.0/modules/calib3d/src/fundam.cpp#L548