pcl::NormalRefinement< NormalT > Class Template Reference

Normal vector refinement class More...

#include <pcl/filters/normal_refinement.h>

Inheritance diagram for pcl::NormalRefinement< NormalT >:

Collaboration diagram for pcl::NormalRefinement< NormalT >:

Public Member Functions
	NormalRefinement ()
	Empty constructor, sets default convergence parameters. More...
	NormalRefinement (const std::vector< Indices > &k_indices, const std::vector< std::vector< float > > &k_sqr_distances)
	Constructor for setting correspondences, sets default convergence parameters. More...
void	setCorrespondences (const std::vector< Indices > &k_indices, const std::vector< std::vector< float > > &k_sqr_distances)
	Set correspondences calculated from nearest neighbor search. More...
void	getCorrespondences (std::vector< Indices > &k_indices, std::vector< std::vector< float > > &k_sqr_distances)
	Get correspondences (copy) More...
void	setMaxIterations (unsigned int max_iterations)
	Set maximum iterations. More...
unsigned int	getMaxIterations ()
	Get maximum iterations. More...
void	setConvergenceThreshold (float convergence_threshold)
	Set convergence threshold. More...
float	getConvergenceThreshold ()
	Get convergence threshold. More...
Public Member Functions inherited from pcl::Filter< NormalT >
	Filter (bool extract_removed_indices=false)
	Empty constructor. More...
IndicesConstPtr const	getRemovedIndices () const
	Get the point indices being removed. More...
void	getRemovedIndices (PointIndices &pi)
	Get the point indices being removed. More...
void	filter (PointCloud &output)
	Calls the filtering method and returns the filtered dataset in output. More...
Public Member Functions inherited from pcl::PCLBase< PointT >
	PCLBase ()
	Empty constructor. More...
	PCLBase (const PCLBase &base)
	Copy constructor. More...
virtual	~PCLBase ()=default
	Destructor. More...
virtual void	setInputCloud (const PointCloudConstPtr &cloud)
	Provide a pointer to the input dataset. More...
PointCloudConstPtr const	getInputCloud () const
	Get a pointer to the input point cloud dataset. More...
virtual void	setIndices (const IndicesPtr &indices)
	Provide a pointer to the vector of indices that represents the input data. More...
virtual void	setIndices (const IndicesConstPtr &indices)
	Provide a pointer to the vector of indices that represents the input data. More...
virtual void	setIndices (const PointIndicesConstPtr &indices)
	Provide a pointer to the vector of indices that represents the input data. More...
virtual void	setIndices (std::size_t row_start, std::size_t col_start, std::size_t nb_rows, std::size_t nb_cols)
	Set the indices for the points laying within an interest region of the point cloud. More...
IndicesPtr	getIndices ()
	Get a pointer to the vector of indices used. More...
IndicesConstPtr const	getIndices () const
	Get a pointer to the vector of indices used. More...
const PointT &	operator[] (std::size_t pos) const
	Override PointCloud operator[] to shorten code. More...

Protected Member Functions
void	applyFilter (PointCloud &output) override
	Filter a Point Cloud. More...
Protected Member Functions inherited from pcl::Filter< NormalT >
const std::string &	getClassName () const
	Get a string representation of the name of this class. More...
Protected Member Functions inherited from pcl::PCLBase< PointT >
bool	initCompute ()
	This method should get called before starting the actual computation. More...
bool	deinitCompute ()
	This method should get called after finishing the actual computation. More...

Additional Inherited Members
Public Types inherited from pcl::Filter< NormalT >
using	Ptr = shared_ptr< Filter< NormalT > >
using	ConstPtr = shared_ptr< const Filter< NormalT > >
using	PointCloud = pcl::PointCloud< NormalT >
using	PointCloudPtr = typename PointCloud::Ptr
using	PointCloudConstPtr = typename PointCloud::ConstPtr
Public Types inherited from pcl::PCLBase< PointT >
using	PointCloud = pcl::PointCloud< PointT >
using	PointCloudPtr = typename PointCloud::Ptr
using	PointCloudConstPtr = typename PointCloud::ConstPtr
using	PointIndicesPtr = PointIndices::Ptr
using	PointIndicesConstPtr = PointIndices::ConstPtr
Protected Attributes inherited from pcl::Filter< NormalT >
IndicesPtr	removed_indices_
	Indices of the points that are removed. More...
std::string	filter_name_
	The filter name. More...
bool	extract_removed_indices_
	Set to true if we want to return the indices of the removed points. More...
Protected Attributes inherited from pcl::PCLBase< PointT >
PointCloudConstPtr	input_
	The input point cloud dataset. More...
IndicesPtr	indices_
	A pointer to the vector of point indices to use. More...
bool	use_indices_
	Set to true if point indices are used. More...
bool	fake_indices_
	If no set of indices are given, we construct a set of fake indices that mimic the input PointCloud. More...

Detailed Description

template<typename NormalT>
class pcl::NormalRefinement< NormalT >

Normal vector refinement class

This class refines a set of already estimated normals by iteratively updating each normal to the (weighted) mean of all normals in its neighborhood. The intention is that you reuse the same point correspondences as used when estimating the original normals in order to avoid repeating a nearest neighbor search.

Note

This class avoids points for which a NaN is encountered in the neighborhood. In the special case where a point has only NaNs in its neighborhood, the resultant refined normal will be set to zero, i.e. this class only produces finite normals.

Usage example:

// Input point cloud
pcl::PointCloud<PointT> cloud;
 
// Fill cloud...
 
// Estimated and refined normals
pcl::PointCloud<NormalT> normals;
pcl::PointCloud<NormalT> normals_refined;
 
// Search parameters
const int k = 5;
std::vector<Indices > k_indices;
std::vector<std::vector<float> > k_sqr_distances;
 
// Run search
pcl::search::KdTree<pcl::PointXYZRGB> search;
search.setInputCloud (cloud.makeShared ());
search.nearestKSearch (cloud, Indices (), k, k_indices, k_sqr_distances);
 
// Use search results for normal estimation
pcl::NormalEstimation<PointT, NormalT> ne;
for (unsigned int i = 0; i < cloud.size (); ++i)
{
  NormalT normal;
  ne.computePointNormal (cloud, k_indices[i]
                         normal.normal_x, normal.normal_y, normal.normal_z, normal.curvature);
  pcl::flipNormalTowardsViewpoint (cloud[i], cloud.sensor_origin_[0], cloud.sensor_origin_[1], cloud.sensor_origin_[2],
                                   normal.normal_x, normal.normal_y, normal.normal_z);
  normals.push_back (normal);
}
 
// Run refinement using search results
pcl::NormalRefinement<NormalT> nr (k_indices, k_sqr_distances);
nr.setInputCloud (normals.makeShared ());
nr.filter (normals_refined);

Author

Anders Glent Buch

Definition at line 194 of file normal_refinement.h.

Constructor & Destructor Documentation

NormalRefinement() [1/2]

template<typename NormalT >

pcl::NormalRefinement< NormalT >::NormalRefinement ( )

inline

Empty constructor, sets default convergence parameters.

Definition at line 207 of file normal_refinement.h.

References pcl::Filter< NormalT >::filter_name_, pcl::NormalRefinement< NormalT >::setConvergenceThreshold(), and pcl::NormalRefinement< NormalT >::setMaxIterations().

NormalRefinement() [2/2]

template<typename NormalT >

pcl::NormalRefinement< NormalT >::NormalRefinement ( const std::vector< Indices > &  k_indices, const std::vector< std::vector< float > > &  k_sqr_distances  )

inline

Constructor for setting correspondences, sets default convergence parameters.

Parameters

k_indices	indices of neighboring points
k_sqr_distances	squared distances to the neighboring points

Definition at line 219 of file normal_refinement.h.

References pcl::Filter< NormalT >::filter_name_, pcl::NormalRefinement< NormalT >::setConvergenceThreshold(), pcl::NormalRefinement< NormalT >::setCorrespondences(), and pcl::NormalRefinement< NormalT >::setMaxIterations().

Member Function Documentation

applyFilter()

template<typename NormalT >

void pcl::NormalRefinement< NormalT >::applyFilter ( PointCloud &  output )

overrideprotectedvirtual

Filter a Point Cloud.

Parameters

output

the resultant point cloud message

Implements pcl::Filter< NormalT >.

Definition at line 48 of file normal_refinement.hpp.

References pcl::refineNormal().

getConvergenceThreshold()

template<typename NormalT >

float pcl::NormalRefinement< NormalT >::getConvergenceThreshold ( )

inline

Get convergence threshold.

Returns

convergence threshold

Definition at line 281 of file normal_refinement.h.

getCorrespondences()

template<typename NormalT >

void pcl::NormalRefinement< NormalT >::getCorrespondences ( std::vector< Indices > &  k_indices, std::vector< std::vector< float > > &  k_sqr_distances  )

inline

Get correspondences (copy)

Parameters

k_indices	indices of neighboring points
k_sqr_distances	squared distances to the neighboring points

Definition at line 244 of file normal_refinement.h.

getMaxIterations()

template<typename NormalT >

unsigned int pcl::NormalRefinement< NormalT >::getMaxIterations ( )

inline

Get maximum iterations.

Returns

maximum iterations

Definition at line 263 of file normal_refinement.h.

setConvergenceThreshold()

template<typename NormalT >

void pcl::NormalRefinement< NormalT >::setConvergenceThreshold ( float  convergence_threshold )

inline

Set convergence threshold.

Parameters

convergence_threshold

convergence threshold

Definition at line 272 of file normal_refinement.h.

Referenced by pcl::NormalRefinement< NormalT >::NormalRefinement().

setCorrespondences()

template<typename NormalT >

void pcl::NormalRefinement< NormalT >::setCorrespondences ( const std::vector< Indices > &  k_indices, const std::vector< std::vector< float > > &  k_sqr_distances  )

inline

Set correspondences calculated from nearest neighbor search.

Parameters

k_indices	indices of neighboring points
k_sqr_distances	squared distances to the neighboring points

Definition at line 233 of file normal_refinement.h.

Referenced by pcl::NormalRefinement< NormalT >::NormalRefinement().

setMaxIterations()

template<typename NormalT >

void pcl::NormalRefinement< NormalT >::setMaxIterations ( unsigned int  max_iterations )

inline

Set maximum iterations.

Parameters

max_iterations

maximum iterations

Definition at line 254 of file normal_refinement.h.

Referenced by pcl::NormalRefinement< NormalT >::NormalRefinement().

---

The documentation for this class was generated from the following files:

• pcl/filters/normal_refinement.h
• pcl/filters/impl/normal_refinement.hpp