transformation_from_correspondences.hpp
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#include <pcl/common/eigen.h>
//////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
inline void
pcl::TransformationFromCorrespondences::reset ()
{
no_of_samples_ = 0;
accumulated_weight_ = 0.0;
mean1_.fill(0);
mean2_.fill(0);
covariance_.fill(0);
}
//////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
inline void
pcl::TransformationFromCorrespondences::add (const Eigen::Vector3f& point, const Eigen::Vector3f& corresponding_point,
float weight)
{
if (weight==0.0f)
return;
++no_of_samples_;
accumulated_weight_ += weight;
float alpha = weight/accumulated_weight_;
Eigen::Vector3f diff1 = point - mean1_, diff2 = corresponding_point - mean2_;
covariance_ = (1.0f-alpha)*(covariance_ + alpha * (diff2 * diff1.transpose()));
mean1_ += alpha*(diff1);
mean2_ += alpha*(diff2);
}
//////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
inline Eigen::Affine3f
pcl::TransformationFromCorrespondences::getTransformation ()
{
//Eigen::JacobiSVD<Eigen::Matrix<float, 3, 3> > svd (covariance_, Eigen::ComputeFullU | Eigen::ComputeFullV);
Eigen::JacobiSVD<Eigen::Matrix<float, 3, 3> > svd (covariance_, Eigen::ComputeFullU | Eigen::ComputeFullV);
const Eigen::Matrix<float, 3, 3>& u = svd.matrixU(),
& v = svd.matrixV();
Eigen::Matrix<float, 3, 3> s;
s.setIdentity();
if (u.determinant()*v.determinant() < 0.0f)
s(2,2) = -1.0f;
Eigen::Matrix<float, 3, 3> r = u * s * v.transpose();
Eigen::Vector3f t = mean2_ - r*mean1_;
Eigen::Affine3f ret;
ret(0,0)=r(0,0); ret(0,1)=r(0,1); ret(0,2)=r(0,2); ret(0,3)=t(0);
ret(1,0)=r(1,0); ret(1,1)=r(1,1); ret(1,2)=r(1,2); ret(1,3)=t(1);
ret(2,0)=r(2,0); ret(2,1)=r(2,1); ret(2,2)=r(2,2); ret(2,3)=t(2);
ret(3,0)=0.0f; ret(3,1)=0.0f; ret(3,2)=0.0f; ret(3,3)=1.0f;
return (ret);
}
pcl::TransformationFromCorrespondences::no_of_samples_
unsigned int no_of_samples_
Definition: transformation_from_correspondences.h:82
pcl::TransformationFromCorrespondences::accumulated_weight_
float accumulated_weight_
Definition: transformation_from_correspondences.h:83
pcl::TransformationFromCorrespondences::reset
void reset()
Reset the object to work with a new data set.
Definition: transformation_from_correspondences.hpp:42
pcl::TransformationFromCorrespondences::covariance_
Eigen::Matrix< float, 3, 3 > covariance_
Definition: transformation_from_correspondences.h:86
pcl::TransformationFromCorrespondences::getTransformation
Eigen::Affine3f getTransformation()
Calculate the transformation that will best transform the points into their correspondences.
Definition: transformation_from_correspondences.hpp:72
pcl::TransformationFromCorrespondences::mean2_
Eigen::Vector3f mean2_
Definition: transformation_from_correspondences.h:85
pcl::TransformationFromCorrespondences::mean1_
Eigen::Vector3f mean1_
Definition: transformation_from_correspondences.h:84
pcl::TransformationFromCorrespondences::add
void add(const Eigen::Vector3f &point, const Eigen::Vector3f &corresponding_point, float weight=1.0)
Add a new sample.
Definition: transformation_from_correspondences.hpp:53