transformation_estimation_svd.hpp
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#ifndef PCL_REGISTRATION_TRANSFORMATION_ESTIMATION_SVD_HPP_
#define PCL_REGISTRATION_TRANSFORMATION_ESTIMATION_SVD_HPP_
#include <pcl/common/eigen.h>
///////////////////////////////////////////////////////////////////////////////////////////
template <typename PointSource, typename PointTarget, typename Scalar> inline void
pcl::registration::TransformationEstimationSVD<PointSource, PointTarget, Scalar>::estimateRigidTransformation (
const pcl::PointCloud<PointSource> &cloud_src,
const pcl::PointCloud<PointTarget> &cloud_tgt,
Matrix4 &transformation_matrix) const
{
size_t nr_points = cloud_src.points.size ();
if (cloud_tgt.points.size () != nr_points)
{
PCL_ERROR ("[pcl::TransformationEstimationSVD::estimateRigidTransformation] Number or points in source (%lu) differs than target (%lu)!\n", nr_points, cloud_tgt.points.size ());
return;
}
ConstCloudIterator<PointSource> source_it (cloud_src);
ConstCloudIterator<PointTarget> target_it (cloud_tgt);
estimateRigidTransformation (source_it, target_it, transformation_matrix);
}
///////////////////////////////////////////////////////////////////////////////////////////
template <typename PointSource, typename PointTarget, typename Scalar> void
pcl::registration::TransformationEstimationSVD<PointSource, PointTarget, Scalar>::estimateRigidTransformation (
const pcl::PointCloud<PointSource> &cloud_src,
const std::vector<int> &indices_src,
const pcl::PointCloud<PointTarget> &cloud_tgt,
Matrix4 &transformation_matrix) const
{
if (indices_src.size () != cloud_tgt.points.size ())
{
PCL_ERROR ("[pcl::TransformationSVD::estimateRigidTransformation] Number or points in source (%lu) differs than target (%lu)!\n", indices_src.size (), cloud_tgt.points.size ());
return;
}
ConstCloudIterator<PointSource> source_it (cloud_src, indices_src);
ConstCloudIterator<PointTarget> target_it (cloud_tgt);
estimateRigidTransformation (source_it, target_it, transformation_matrix);
}
///////////////////////////////////////////////////////////////////////////////////////////
template <typename PointSource, typename PointTarget, typename Scalar> inline void
pcl::registration::TransformationEstimationSVD<PointSource, PointTarget, Scalar>::estimateRigidTransformation (
const pcl::PointCloud<PointSource> &cloud_src,
const std::vector<int> &indices_src,
const pcl::PointCloud<PointTarget> &cloud_tgt,
const std::vector<int> &indices_tgt,
Matrix4 &transformation_matrix) const
{
if (indices_src.size () != indices_tgt.size ())
{
PCL_ERROR ("[pcl::TransformationEstimationSVD::estimateRigidTransformation] Number or points in source (%lu) differs than target (%lu)!\n", indices_src.size (), indices_tgt.size ());
return;
}
ConstCloudIterator<PointSource> source_it (cloud_src, indices_src);
ConstCloudIterator<PointTarget> target_it (cloud_tgt, indices_tgt);
estimateRigidTransformation (source_it, target_it, transformation_matrix);
}
///////////////////////////////////////////////////////////////////////////////////////////
template <typename PointSource, typename PointTarget, typename Scalar> void
pcl::registration::TransformationEstimationSVD<PointSource, PointTarget, Scalar>::estimateRigidTransformation (
const pcl::PointCloud<PointSource> &cloud_src,
const pcl::PointCloud<PointTarget> &cloud_tgt,
const pcl::Correspondences &correspondences,
Matrix4 &transformation_matrix) const
{
ConstCloudIterator<PointSource> source_it (cloud_src, correspondences, true);
ConstCloudIterator<PointTarget> target_it (cloud_tgt, correspondences, false);
estimateRigidTransformation (source_it, target_it, transformation_matrix);
}
///////////////////////////////////////////////////////////////////////////////////////////
template <typename PointSource, typename PointTarget, typename Scalar> inline void
pcl::registration::TransformationEstimationSVD<PointSource, PointTarget, Scalar>::estimateRigidTransformation (
ConstCloudIterator<PointSource>& source_it,
ConstCloudIterator<PointTarget>& target_it,
Matrix4 &transformation_matrix) const
{
// Convert to Eigen format
const int npts = static_cast <int> (source_it.size ());
if (use_umeyama_)
{
Eigen::Matrix<Scalar, 3, Eigen::Dynamic> cloud_src (3, npts);
Eigen::Matrix<Scalar, 3, Eigen::Dynamic> cloud_tgt (3, npts);
for (int i = 0; i < npts; ++i)
{
cloud_src (0, i) = source_it->x;
cloud_src (1, i) = source_it->y;
cloud_src (2, i) = source_it->z;
++source_it;
cloud_tgt (0, i) = target_it->x;
cloud_tgt (1, i) = target_it->y;
cloud_tgt (2, i) = target_it->z;
++target_it;
}
// Call Umeyama directly from Eigen (PCL patched version until Eigen is released)
transformation_matrix = pcl::umeyama (cloud_src, cloud_tgt, false);
}
else
{
source_it.reset (); target_it.reset ();
// <cloud_src,cloud_src> is the source dataset
transformation_matrix.setIdentity ();
Eigen::Matrix<Scalar, 4, 1> centroid_src, centroid_tgt;
// Estimate the centroids of source, target
compute3DCentroid (source_it, centroid_src);
compute3DCentroid (target_it, centroid_tgt);
source_it.reset (); target_it.reset ();
// Subtract the centroids from source, target
Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic> cloud_src_demean, cloud_tgt_demean;
demeanPointCloud (source_it, centroid_src, cloud_src_demean);
demeanPointCloud (target_it, centroid_tgt, cloud_tgt_demean);
getTransformationFromCorrelation (cloud_src_demean, centroid_src, cloud_tgt_demean, centroid_tgt, transformation_matrix);
}
}
///////////////////////////////////////////////////////////////////////////////////////////
template <typename PointSource, typename PointTarget, typename Scalar> void
pcl::registration::TransformationEstimationSVD<PointSource, PointTarget, Scalar>::getTransformationFromCorrelation (
const Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic> &cloud_src_demean,
const Eigen::Matrix<Scalar, 4, 1> &centroid_src,
const Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic> &cloud_tgt_demean,
const Eigen::Matrix<Scalar, 4, 1> &centroid_tgt,
Matrix4 &transformation_matrix) const
{
transformation_matrix.setIdentity ();
// Assemble the correlation matrix H = source * target'
Eigen::Matrix<Scalar, 3, 3> H = (cloud_src_demean * cloud_tgt_demean.transpose ()).topLeftCorner (3, 3);
// Compute the Singular Value Decomposition
Eigen::JacobiSVD<Eigen::Matrix<Scalar, 3, 3> > svd (H, Eigen::ComputeFullU | Eigen::ComputeFullV);
Eigen::Matrix<Scalar, 3, 3> u = svd.matrixU ();
Eigen::Matrix<Scalar, 3, 3> v = svd.matrixV ();
// Compute R = V * U'
if (u.determinant () * v.determinant () < 0)
{
for (int x = 0; x < 3; ++x)
v (x, 2) *= -1;
}
Eigen::Matrix<Scalar, 3, 3> R = v * u.transpose ();
// Return the correct transformation
transformation_matrix.topLeftCorner (3, 3) = R;
const Eigen::Matrix<Scalar, 3, 1> Rc (R * centroid_src.head (3));
transformation_matrix.block (0, 3, 3, 1) = centroid_tgt.head (3) - Rc;
}
//#define PCL_INSTANTIATE_TransformationEstimationSVD(T,U) template class PCL_EXPORTS pcl::registration::TransformationEstimationSVD<T,U>;
#endif /* PCL_REGISTRATION_TRANSFORMATION_ESTIMATION_SVD_HPP_ */
pcl::ConstCloudIterator
Iterator class for point clouds with or without given indices.
Definition: cloud_iterator.h:121
pcl::PointCloud::points
std::vector< PointT, Eigen::aligned_allocator< PointT > > points
The point data.
Definition: point_cloud.h:410
pcl::umeyama
Eigen::internal::umeyama_transform_matrix_type< Derived, OtherDerived >::type umeyama(const Eigen::MatrixBase< Derived > &src, const Eigen::MatrixBase< OtherDerived > &dst, bool with_scaling=false)
Returns the transformation between two point sets.
Definition: eigen.hpp:739
pcl::ConstCloudIterator::size
size_t size() const
Size of the range the iterator is going through.
Definition: cloud_iterator.hpp:537
pcl::demeanPointCloud
void demeanPointCloud(ConstCloudIterator< PointT > &cloud_iterator, const Eigen::Matrix< Scalar, 4, 1 > &centroid, pcl::PointCloud< PointT > &cloud_out, int npts=0)
Subtract a centroid from a point cloud and return the de-meaned representation.
Definition: centroid.hpp:631
pcl::Correspondences
std::vector< pcl::Correspondence, Eigen::aligned_allocator< pcl::Correspondence > > Correspondences
Definition: correspondence.h:92
pcl::ConstCloudIterator::reset
void reset()
Definition: cloud_iterator.hpp:544
pcl::registration::TransformationEstimation< PointT, PointT, Scalar >::Matrix4
Eigen::Matrix< Scalar, 4, 4 > Matrix4
Definition: transformation_estimation.h:65
pcl::PointCloud< PointSource >
pcl::registration::TransformationEstimationSVD::getTransformationFromCorrelation
virtual void getTransformationFromCorrelation(const Eigen::Matrix< Scalar, Eigen::Dynamic, Eigen::Dynamic > &cloud_src_demean, const Eigen::Matrix< Scalar, 4, 1 > &centroid_src, const Eigen::Matrix< Scalar, Eigen::Dynamic, Eigen::Dynamic > &cloud_tgt_demean, const Eigen::Matrix< Scalar, 4, 1 > &centroid_tgt, Matrix4 &transformation_matrix) const
Obtain a 4x4 rigid transformation matrix from a correlation matrix H = src * tgt&#39;.
Definition: transformation_estimation_svd.hpp:172
pcl::registration::TransformationEstimationSVD::estimateRigidTransformation
void estimateRigidTransformation(const pcl::PointCloud< PointSource > &cloud_src, const pcl::PointCloud< PointTarget > &cloud_tgt, Matrix4 &transformation_matrix) const
Estimate a rigid rotation transformation between a source and a target point cloud using SVD...
Definition: transformation_estimation_svd.hpp:47
pcl::compute3DCentroid
unsigned int compute3DCentroid(ConstCloudIterator< PointT > &cloud_iterator, Eigen::Matrix< Scalar, 4, 1 > &centroid)
Compute the 3D (X-Y-Z) centroid of a set of points and return it as a 3D vector.
Definition: centroid.hpp:50