Ransac Distance Model in pure rotation motion for Eigensolver Sac problem

[ckchng]

void
opengv::sac_problems::
relative_pose::EigensolverSacProblem::getSelectedDistancesToModel(
const model_t & model,
const std::vector & indices,
std::vector & scores) const
{
/double referenceNorm = model.translation.norm();
double pureRotation_threshold = 0.0001;
double tanAlpha_threshold = tan(0.002);
double norm_threshold = 0.001;//0.000625
for(size_t i = 0; i < indices.size(); i++)
{
bearingVector_t f1 = _adapter.getBearingVector1(indices[i]);
bearingVector_t f2 = _adapter.getBearingVector2(indices[i]);
Eigen::Vector3d n = f1.cross(model.rotationf2);
if( referenceNorm > pureRotation_threshold )
{
double np_norm = n.transpose() * model.eigenvectors.col(0);
Eigen::Vector3d np = np_norm * model.eigenvectors.col(0);
Eigen::Vector3d no = n - np;
double maxDistance = norm_threshold + tanAlpha_threshold * no.norm();
scores.push_back(np.norm()/maxDistance);
}
else
scores.push_back(n.norm()/norm_threshold);
}*/

translation_t tempTranslation = _adapter.gett12();
rotation_t tempRotation = _adapter.getR12();

translation_t translation = model.translation;
rotation_t rotation = model.rotation;
_adapter.sett12(translation);
_adapter.setR12(rotation);

transformation_t inverseSolution;
inverseSolution.block<3,3>(0,0) = rotation.transpose();
inverseSolution.col(3) = -inverseSolution.block<3,3>(0,0)*translation;

Eigen::Matrix<double,4,1> p_hom;
p_hom[3] = 1.0;

for( size_t i = 0; i < indices.size(); i++ )
{
p_hom.block<3,1>(0,0) =
opengv::triangulation::triangulate2(_adapter,indices[i]);
bearingVector_t reprojection1 = p_hom.block<3,1>(0,0);
bearingVector_t reprojection2 = inverseSolution * p_hom;
reprojection1 = reprojection1 / reprojection1.norm();
reprojection2 = reprojection2 / reprojection2.norm();
bearingVector_t f1 = _adapter.getBearingVector1(indices[i]);
bearingVector_t f2 = _adapter.getBearingVector2(indices[i]);

//bearing-vector based outlier criterium (select threshold accordingly):
//1-(f1'*f2) = 1-cos(alpha) \in [0:2]
double reprojError1 = 1.0 - (f1.transpose() * reprojection1);
double reprojError2 = 1.0 - (f2.transpose() * reprojection2);
scores.push_back(reprojError1 + reprojError2);

}

_adapter.sett12(tempTranslation);
_adapter.setR12(tempRotation);
}

I realize that the first part of the code was commented out. It seems to be dealing with pure rotation motion. If I understand correctly, the 'triangulate2' is not going to project the points properly under pure rotation motion right?

[philipzimmermann]

I noticed that the outlier threshold for the RotationOnlySacProblem doesn't have any influence on the outliers. Could this have to do with this?