public void Test_Triangulation_NoNoise()
{
// 1) We have P, P', F, e, e'
CreateCameraMatrices();
CreateEpiGeometry();
// 2) Create set of 3d points in sensible range
// 3) Project them onto 2 images using P and P'
GeneratePoints_Random(_seed);
// 4) Using pairs of corresponding points find their 3D back-projection with Triangulation
TwoPointsTriangulation trangulation = new TwoPointsTriangulation();
trangulation.CameraLeft = _CM_L;
trangulation.CameraRight = _CM_R;
trangulation.EpipoleLeft = _epi_L;
trangulation.EpipoleRight = _epi_R;
trangulation.Fundamental = _F;
trangulation.PointsLeft = _imagePointsLeft;
trangulation.PointsRight = _imagePointsRight;
trangulation.Estimate3DPoints();
var ePoints3D = trangulation.Points3D;
for(int i = 0; i < _pointsCount; ++i)
{
var errVec = ePoints3D[i].PointwiseDivide_NoNaN(_realPoints[i]);
double err = (errVec - DenseVector.Create(4, 1.0)).L2Norm();
Assert.IsTrue(
err < 0.2 || // max 2% diffrence
(ePoints3D[i] - _realPoints[i]).L2Norm() < 10);
}
// 5) Repeat adding some noise to image coords (matching error)
// 6) Repeat adding some noise to camera matrix (calibration error)
// 7) Repeat adding some noise to camera matrix and matched image coords (theoreticaly this is case close to real one)
}
public void Test_Triangulation_NoiseImageOnly()
{
// 1) We have P, P', F, e, e'
CreateCameraMatrices();
GeneratePoints_Random(_seed);
NormalisePoints();
CreateEpiGeometry_Normalized();
// 2) Create set of 3d points in sensible range
// 3) Project them onto 2 images using P and P'
var noisedLeft = AddNoise(_imgPointsNormLeft, 1e-6);
var noisedRight = AddNoise(_imgPointsNormRight, 1e-6);
// 4) Using pairs of corresponding points find their 3D back-projection with Triangulation
TwoPointsTriangulation trangulation = new TwoPointsTriangulation();
trangulation.CameraLeft = _CMN_L;
trangulation.CameraRight = _CMN_R;
trangulation.EpipoleLeft = _epi_L;
trangulation.EpipoleRight = _epi_R;
trangulation.Fundamental = _F;
trangulation.PointsLeft = noisedLeft;
trangulation.PointsRight = noisedRight;
trangulation.Estimate3DPoints();
var ePoints3D = trangulation.Points3D;
for(int i = 0; i < _pointsCount; ++i)
{
trangulation._pL = noisedLeft[i];
trangulation._pR = noisedRight[i];
// trangulation.ComputeBackprojected3DPoint();
var point3d = trangulation._p3D; // To compare with linear
var realPoint = _realPointsNorm[i];
var ep3d = ePoints3D[i];
var elin = (point3d - realPoint);
var errVec = ePoints3D[i].PointwiseDivide_NoNaN(_realPointsNorm[i]);
double err = (errVec - DenseVector.Create(4, 1.0)).L2Norm();
double err2 = (ePoints3D[i] - _realPointsNorm[i]).L2Norm();
double errlin = (point3d - realPoint).L2Norm();
// Assert.IsTrue(
// err < 0.2 || // max 2% diffrence
// (ePoints3D[i] - _realPoints[i]).L2Norm() < 10);
}
}