Point Cloud Library (PCL)  1.14.1-dev
List of all members | Public Types | Public Member Functions | Protected Member Functions
pcl::LinearLeastSquaresNormalEstimation< PointInT, PointOutT > Class Template Reference

Surface normal estimation on dense data using a least-squares estimation based on a first-order Taylor approximation. More...

#include <pcl/features/linear_least_squares_normal.h>

+ Inheritance diagram for pcl::LinearLeastSquaresNormalEstimation< PointInT, PointOutT >:
+ Collaboration diagram for pcl::LinearLeastSquaresNormalEstimation< PointInT, PointOutT >:

Public Types

using Ptr = shared_ptr< LinearLeastSquaresNormalEstimation< PointInT, PointOutT > >
 
using ConstPtr = shared_ptr< const LinearLeastSquaresNormalEstimation< PointInT, PointOutT > >
 
using PointCloudIn = typename Feature< PointInT, PointOutT >::PointCloudIn
 
using PointCloudOut = typename Feature< PointInT, PointOutT >::PointCloudOut
 
- Public Types inherited from pcl::Feature< PointInT, PointOutT >
using BaseClass = PCLBase< PointInT >
 
using Ptr = shared_ptr< Feature< PointInT, PointOutT > >
 
using ConstPtr = shared_ptr< const Feature< PointInT, PointOutT > >
 
using KdTree = pcl::search::Search< PointInT >
 
using KdTreePtr = typename KdTree::Ptr
 
using PointCloudIn = pcl::PointCloud< PointInT >
 
using PointCloudInPtr = typename PointCloudIn::Ptr
 
using PointCloudInConstPtr = typename PointCloudIn::ConstPtr
 
using PointCloudOut = pcl::PointCloud< PointOutT >
 
using SearchMethod = std::function< int(std::size_t, double, pcl::Indices &, std::vector< float > &)>
 
using SearchMethodSurface = std::function< int(const PointCloudIn &cloud, std::size_t index, double, pcl::Indices &, std::vector< float > &)>
 
- Public Types inherited from pcl::PCLBase< PointInT >
using PointCloud = pcl::PointCloud< PointInT >
 
using PointCloudPtr = typename PointCloud::Ptr
 
using PointCloudConstPtr = typename PointCloud::ConstPtr
 
using PointIndicesPtr = PointIndices::Ptr
 
using PointIndicesConstPtr = PointIndices::ConstPtr
 

Public Member Functions

 LinearLeastSquaresNormalEstimation ()
 Constructor. More...
 
 ~LinearLeastSquaresNormalEstimation () override
 Destructor. More...
 
void computePointNormal (const int pos_x, const int pos_y, PointOutT &normal)
 Computes the normal at the specified position. More...
 
void setNormalSmoothingSize (float normal_smoothing_size)
 Set the normal smoothing size. More...
 
void setDepthDependentSmoothing (bool use_depth_dependent_smoothing)
 Set whether to use depth depending smoothing or not. More...
 
void setMaxDepthChangeFactor (float max_depth_change_factor)
 The depth change threshold for computing object borders. More...
 
void setInputCloud (const typename PointCloudIn::ConstPtr &cloud) override
 Provide a pointer to the input dataset (overwrites the PCLBase::setInputCloud method) More...
 
- Public Member Functions inherited from pcl::Feature< PointInT, PointOutT >
 Feature ()
 Empty constructor. More...
 
void setSearchSurface (const PointCloudInConstPtr &cloud)
 Provide a pointer to a dataset to add additional information to estimate the features for every point in the input dataset. More...
 
PointCloudInConstPtr getSearchSurface () const
 Get a pointer to the surface point cloud dataset. More...
 
void setSearchMethod (const KdTreePtr &tree)
 Provide a pointer to the search object. More...
 
KdTreePtr getSearchMethod () const
 Get a pointer to the search method used. More...
 
double getSearchParameter () const
 Get the internal search parameter. More...
 
void setKSearch (int k)
 Set the number of k nearest neighbors to use for the feature estimation. More...
 
int getKSearch () const
 get the number of k nearest neighbors used for the feature estimation. More...
 
void setRadiusSearch (double radius)
 Set the sphere radius that is to be used for determining the nearest neighbors used for the feature estimation. More...
 
double getRadiusSearch () const
 Get the sphere radius used for determining the neighbors. More...
 
void compute (PointCloudOut &output)
 Base method for feature estimation for all points given in <setInputCloud (), setIndices ()> using the surface in setSearchSurface () and the spatial locator in setSearchMethod () More...
 
- Public Member Functions inherited from pcl::PCLBase< PointInT >
 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 PointInT & operator[] (std::size_t pos) const
 Override PointCloud operator[] to shorten code. More...
 

Protected Member Functions

void computeFeature (PointCloudOut &output) override
 Computes the normal for the complete cloud. More...
 
- Protected Member Functions inherited from pcl::Feature< PointInT, PointOutT >
const std::string & getClassName () const
 Get a string representation of the name of this class. More...
 
virtual bool initCompute ()
 This method should get called before starting the actual computation. More...
 
virtual bool deinitCompute ()
 This method should get called after ending the actual computation. More...
 
int searchForNeighbors (std::size_t index, double parameter, pcl::Indices &indices, std::vector< float > &distances) const
 Search for k-nearest neighbors using the spatial locator from setSearchmethod, and the given surface from setSearchSurface. More...
 
int searchForNeighbors (const PointCloudIn &cloud, std::size_t index, double parameter, pcl::Indices &indices, std::vector< float > &distances) const
 Search for k-nearest neighbors using the spatial locator from setSearchmethod, and the given surface from setSearchSurface. More...
 
- Protected Member Functions inherited from pcl::PCLBase< PointInT >
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

- Protected Attributes inherited from pcl::Feature< PointInT, PointOutT >
std::string feature_name_
 The feature name. More...
 
SearchMethodSurface search_method_surface_
 The search method template for points. More...
 
PointCloudInConstPtr surface_
 An input point cloud describing the surface that is to be used for nearest neighbors estimation. More...
 
KdTreePtr tree_
 A pointer to the spatial search object. More...
 
double search_parameter_
 The actual search parameter (from either search_radius_ or k_). More...
 
double search_radius_
 The nearest neighbors search radius for each point. More...
 
int k_
 The number of K nearest neighbors to use for each point. More...
 
bool fake_surface_
 If no surface is given, we use the input PointCloud as the surface. More...
 
- Protected Attributes inherited from pcl::PCLBase< PointInT >
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 PointInT, typename PointOutT>
class pcl::LinearLeastSquaresNormalEstimation< PointInT, PointOutT >

Surface normal estimation on dense data using a least-squares estimation based on a first-order Taylor approximation.

Author
Stefan Holzer, Cedric Cagniart

Definition at line 49 of file linear_least_squares_normal.h.

Member Typedef Documentation

◆ ConstPtr

template<typename PointInT , typename PointOutT >
using pcl::LinearLeastSquaresNormalEstimation< PointInT, PointOutT >::ConstPtr = shared_ptr<const LinearLeastSquaresNormalEstimation<PointInT, PointOutT> >

Definition at line 53 of file linear_least_squares_normal.h.

◆ PointCloudIn

template<typename PointInT , typename PointOutT >
using pcl::LinearLeastSquaresNormalEstimation< PointInT, PointOutT >::PointCloudIn = typename Feature<PointInT, PointOutT>::PointCloudIn

Definition at line 54 of file linear_least_squares_normal.h.

◆ PointCloudOut

template<typename PointInT , typename PointOutT >
using pcl::LinearLeastSquaresNormalEstimation< PointInT, PointOutT >::PointCloudOut = typename Feature<PointInT, PointOutT>::PointCloudOut

Definition at line 55 of file linear_least_squares_normal.h.

◆ Ptr

template<typename PointInT , typename PointOutT >
using pcl::LinearLeastSquaresNormalEstimation< PointInT, PointOutT >::Ptr = shared_ptr<LinearLeastSquaresNormalEstimation<PointInT, PointOutT> >

Definition at line 52 of file linear_least_squares_normal.h.

Constructor & Destructor Documentation

◆ LinearLeastSquaresNormalEstimation()

template<typename PointInT , typename PointOutT >
pcl::LinearLeastSquaresNormalEstimation< PointInT, PointOutT >::LinearLeastSquaresNormalEstimation ( )
inline

◆ ~LinearLeastSquaresNormalEstimation()

template<typename PointInT , typename PointOutT >
pcl::LinearLeastSquaresNormalEstimation< PointInT, PointOutT >::~LinearLeastSquaresNormalEstimation ( )
overridedefault

Destructor.

Member Function Documentation

◆ computeFeature()

template<typename PointInT , typename PointOutT >
void pcl::LinearLeastSquaresNormalEstimation< PointInT, PointOutT >::computeFeature ( PointCloudOut output)
overrideprotectedvirtual

Computes the normal for the complete cloud.

Parameters
[out]outputthe resultant normals

Implements pcl::Feature< PointInT, PointOutT >.

Definition at line 153 of file linear_least_squares_normal.hpp.

◆ computePointNormal()

template<typename PointInT , typename PointOutT >
void pcl::LinearLeastSquaresNormalEstimation< PointInT, PointOutT >::computePointNormal ( const int  pos_x,
const int  pos_y,
PointOutT &  normal 
)

Computes the normal at the specified position.

Parameters
[in]pos_xx position (pixel)
[in]pos_yy position (pixel)
[out]normalthe output estimated normal

Definition at line 51 of file linear_least_squares_normal.hpp.

◆ setDepthDependentSmoothing()

template<typename PointInT , typename PointOutT >
void pcl::LinearLeastSquaresNormalEstimation< PointInT, PointOutT >::setDepthDependentSmoothing ( bool  use_depth_dependent_smoothing)
inline

Set whether to use depth depending smoothing or not.

Parameters
[in]use_depth_dependent_smoothingdecides whether the smoothing is depth dependent

Definition at line 94 of file linear_least_squares_normal.h.

Referenced by pcl::SurfaceNormalModality< PointInT >::computeSurfaceNormals().

◆ setInputCloud()

template<typename PointInT , typename PointOutT >
void pcl::LinearLeastSquaresNormalEstimation< PointInT, PointOutT >::setInputCloud ( const typename PointCloudIn::ConstPtr cloud)
inlineoverride

Provide a pointer to the input dataset (overwrites the PCLBase::setInputCloud method)

Parameters
[in]cloudthe const boost shared pointer to a PointCloud message

Definition at line 113 of file linear_least_squares_normal.h.

References pcl::PCLBase< PointInT >::input_.

Referenced by pcl::SurfaceNormalModality< PointInT >::computeSurfaceNormals().

◆ setMaxDepthChangeFactor()

template<typename PointInT , typename PointOutT >
void pcl::LinearLeastSquaresNormalEstimation< PointInT, PointOutT >::setMaxDepthChangeFactor ( float  max_depth_change_factor)
inline

The depth change threshold for computing object borders.

Parameters
[in]max_depth_change_factorthe depth change threshold for computing object borders based on depth changes

Definition at line 104 of file linear_least_squares_normal.h.

Referenced by pcl::SurfaceNormalModality< PointInT >::computeSurfaceNormals().

◆ setNormalSmoothingSize()

template<typename PointInT , typename PointOutT >
void pcl::LinearLeastSquaresNormalEstimation< PointInT, PointOutT >::setNormalSmoothingSize ( float  normal_smoothing_size)
inline

Set the normal smoothing size.

Parameters
[in]normal_smoothing_sizefactor which influences the size of the area used to smooth normals (depth dependent if useDepthDependentSmoothing is true)

Definition at line 85 of file linear_least_squares_normal.h.

Referenced by pcl::SurfaceNormalModality< PointInT >::computeSurfaceNormals().


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