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Normal vector refinement class More...

#include <pcl/filters/normal_refinement.h>

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...
const IndicesConstPtr 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< NormalT >
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...
const PointCloudConstPtr 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...
const IndicesConstPtr getIndices () const
Get a pointer to the vector of indices used. More...
const NormalT & 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 >
virtual void applyFilter (PointCloud &output)=0
Abstract filter method. More...
const std::string & getClassName () const
Get a string representation of the name of this class. More...
- Protected Member Functions inherited from pcl::PCLBase< NormalT >
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< NormalT >
using PointCloud = pcl::PointCloud< NormalT >
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< NormalT >
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
// Fill cloud...
// Estimated and refined 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
search.setInputCloud (cloud.makeShared ());
search.nearestKSearch (cloud, Indices (), k, k_indices, k_sqr_distances);
// Use search results for normal estimation
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);
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 190 of file normal_refinement.h.

Constructor & Destructor Documentation

NormalRefinement() [1/2]

template<typename NormalT >
pcl::NormalRefinement< NormalT >::NormalRefinement ( )
inline

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 215 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 )
overrideprotected

Filter a Point Cloud.

Parameters
output the resultant point cloud message

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 277 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 240 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 259 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 268 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 229 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 250 of file normal_refinement.h.

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


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

© 2009–2012, Willow Garage, Inc.
© 2012–, Open Perception, Inc.
Licensed under the BSD License.
https://pointclouds.org/documentation/classpcl_1_1_normal_refinement.html