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sac_model_normal_sphere.hpp
/*
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* Point Cloud Library (PCL) - www.pointclouds.org
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* $Id: sac_model_normal_sphere.hpp schrandt $
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#ifndef PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_NORMAL_SPHERE_H_
#define PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_NORMAL_SPHERE_H_
#include <pcl/sample_consensus/sac_model_normal_sphere.h>
#include <pcl/common/common.h> // for getAngle3D
//////////////////////////////////////////////////////////////////////////////////////////////////////////////////
template <typename PointT, typename PointNT> void
pcl::SampleConsensusModelNormalSphere<PointT, PointNT>::selectWithinDistance (
const Eigen::VectorXf &model_coefficients, const double threshold, Indices &inliers)
{
if (!normals_)
{
PCL_ERROR ("[pcl::SampleConsensusModelNormalSphere::selectWithinDistance] No input dataset containing normals was given! Use setInputNormals\n");
inliers.clear ();
return;
}
// Check if the model is valid given the user constraints
if (!isModelValid (model_coefficients))
{
inliers.clear ();
return;
}
// Obtain the sphere center
Eigen::Vector4f center = model_coefficients;
center[3] = 0.0f;
inliers.clear ();
error_sqr_dists_.clear ();
inliers.reserve (indices_->size ());
error_sqr_dists_.reserve (indices_->size ());
// Iterate through the 3d points and calculate the distances from them to the sphere
for (std::size_t i = 0; i < indices_->size (); ++i)
{
// Calculate the distance from the point to the sphere center as the difference between
// dist(point,sphere_origin) and sphere_radius
Eigen::Vector4f p ((*input_)[(*indices_)[i]].x,
(*input_)[(*indices_)[i]].y,
(*input_)[(*indices_)[i]].z,
0.0f);
Eigen::Vector4f n_dir = p - center;
const double weighted_euclid_dist = (1.0 - normal_distance_weight_) * std::abs (n_dir.norm () - model_coefficients[3]);
if (weighted_euclid_dist > threshold) // Early termination: cannot be an inlier
continue;
// Calculate the angular distance between the point normal and the sphere normal
Eigen::Vector4f n ((*normals_)[(*indices_)[i]].normal[0],
(*normals_)[(*indices_)[i]].normal[1],
(*normals_)[(*indices_)[i]].normal[2],
0.0f);
double d_normal = std::abs (getAngle3D (n, n_dir));
d_normal = (std::min) (d_normal, M_PI - d_normal);
double distance = std::abs (normal_distance_weight_ * d_normal + weighted_euclid_dist);
if (distance < threshold)
{
// Returns the indices of the points whose distances are smaller than the threshold
inliers.push_back ((*indices_)[i]);
error_sqr_dists_.push_back (static_cast<double> (distance));
}
}
}
//////////////////////////////////////////////////////////////////////////////////////////////////////////////////
template <typename PointT, typename PointNT> std::size_t
pcl::SampleConsensusModelNormalSphere<PointT, PointNT>::countWithinDistance (
const Eigen::VectorXf &model_coefficients, const double threshold) const
{
if (!normals_)
{
PCL_ERROR ("[pcl::SampleConsensusModelNormalSphere::getDistancesToModel] No input dataset containing normals was given! Use setInputNormals\n");
return (0);
}
// Check if the model is valid given the user constraints
if (!isModelValid (model_coefficients))
return(0);
// Obtain the sphere centroid
Eigen::Vector4f center = model_coefficients;
center[3] = 0.0f;
std::size_t nr_p = 0;
// Iterate through the 3d points and calculate the distances from them to the sphere
for (std::size_t i = 0; i < indices_->size (); ++i)
{
// Calculate the distance from the point to the sphere centroid as the difference between
// dist(point,sphere_origin) and sphere_radius
Eigen::Vector4f p ((*input_)[(*indices_)[i]].x,
(*input_)[(*indices_)[i]].y,
(*input_)[(*indices_)[i]].z,
0.0f);
Eigen::Vector4f n_dir = (p-center);
const double weighted_euclid_dist = (1.0 - normal_distance_weight_) * std::abs (n_dir.norm () - model_coefficients[3]);
if (weighted_euclid_dist > threshold) // Early termination: cannot be an inlier
continue;
// Calculate the angular distance between the point normal and the sphere normal
Eigen::Vector4f n ((*normals_)[(*indices_)[i]].normal[0],
(*normals_)[(*indices_)[i]].normal[1],
(*normals_)[(*indices_)[i]].normal[2],
0.0f);
double d_normal = std::abs (getAngle3D (n, n_dir));
d_normal = (std::min) (d_normal, M_PI - d_normal);
if (std::abs (normal_distance_weight_ * d_normal + weighted_euclid_dist) < threshold)
nr_p++;
}
return (nr_p);
}
//////////////////////////////////////////////////////////////////////////////////////////////////////////////////
template <typename PointT, typename PointNT> void
pcl::SampleConsensusModelNormalSphere<PointT, PointNT>::getDistancesToModel (
const Eigen::VectorXf &model_coefficients, std::vector<double> &distances) const
{
if (!normals_)
{
PCL_ERROR ("[pcl::SampleConsensusModelNormalSphere::getDistancesToModel] No input dataset containing normals was given! Use setInputNormals\n");
return;
}
// Check if the model is valid given the user constraints
if (!isModelValid (model_coefficients))
{
distances.clear ();
return;
}
// Obtain the sphere centroid
Eigen::Vector4f center = model_coefficients;
center[3] = 0.0f;
distances.resize (indices_->size ());
// Iterate through the 3d points and calculate the distances from them to the sphere
for (std::size_t i = 0; i < indices_->size (); ++i)
{
// Calculate the distance from the point to the sphere as the difference between
// dist(point,sphere_origin) and sphere_radius
Eigen::Vector4f p ((*input_)[(*indices_)[i]].x,
(*input_)[(*indices_)[i]].y,
(*input_)[(*indices_)[i]].z,
0.0f);
Eigen::Vector4f n_dir = (p-center);
const double weighted_euclid_dist = (1.0 - normal_distance_weight_) * std::abs (n_dir.norm () - model_coefficients[3]);
// Calculate the angular distance between the point normal and the sphere normal
Eigen::Vector4f n ((*normals_)[(*indices_)[i]].normal[0],
(*normals_)[(*indices_)[i]].normal[1],
(*normals_)[(*indices_)[i]].normal[2],
0.0f);
double d_normal = std::abs (getAngle3D (n, n_dir));
d_normal = (std::min) (d_normal, M_PI - d_normal);
distances[i] = std::abs (normal_distance_weight_ * d_normal + weighted_euclid_dist);
}
}
#define PCL_INSTANTIATE_SampleConsensusModelNormalSphere(PointT, PointNT) template class PCL_EXPORTS pcl::SampleConsensusModelNormalSphere<PointT, PointNT>;
#endif // PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_NORMAL_SPHERE_H_
pcl::SampleConsensusModelNormalSphere::selectWithinDistance
void selectWithinDistance(const Eigen::VectorXf &model_coefficients, const double threshold, Indices &inliers) override
Select all the points which respect the given model coefficients as inliers.
Definition sac_model_normal_sphere.hpp:49
pcl::SampleConsensusModelNormalSphere::countWithinDistance
std::size_t countWithinDistance(const Eigen::VectorXf &model_coefficients, const double threshold) const override
Count all the points which respect the given model coefficients as inliers.
Definition sac_model_normal_sphere.hpp:110
pcl::SampleConsensusModelNormalSphere::getDistancesToModel
void getDistancesToModel(const Eigen::VectorXf &model_coefficients, std::vector< double > &distances) const override
Compute all distances from the cloud data to a given sphere model.
Definition sac_model_normal_sphere.hpp:161
common.h
Define standard C methods and C++ classes that are common to all methods.
pcl::getAngle3D
double getAngle3D(const Eigen::Vector4f &v1, const Eigen::Vector4f &v2, const bool in_degree=false)
Compute the smallest angle between two 3D vectors in radians (default) or degree.
Definition common.hpp:47
pcl::Indices
IndicesAllocator<> Indices
Type used for indices in PCL.
Definition types.h:133
M_PI
#define M_PI
Definition pcl_macros.h:203