Point Cloud Library (PCL) 1.12.0
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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>
Public Member Functions | |
LinearLeastSquaresNormalEstimation () | |
Constructor. | |
~LinearLeastSquaresNormalEstimation () | |
Destructor. | |
void | computePointNormal (const int pos_x, const int pos_y, PointOutT &normal) |
Computes the normal at the specified position. | |
void | setNormalSmoothingSize (float normal_smoothing_size) |
Set the normal smoothing size. | |
void | setDepthDependentSmoothing (bool use_depth_dependent_smoothing) |
Set whether to use depth depending smoothing or not. | |
void | setMaxDepthChangeFactor (float max_depth_change_factor) |
The depth change threshold for computing object borders. | |
void | setInputCloud (const typename PointCloudIn::ConstPtr &cloud) override |
Provide a pointer to the input dataset (overwrites the PCLBase::setInputCloud method) | |
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Feature () | |
Empty constructor. | |
virtual | ~Feature () |
Empty destructor. | |
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. | |
PointCloudInConstPtr | getSearchSurface () const |
Get a pointer to the surface point cloud dataset. | |
void | setSearchMethod (const KdTreePtr &tree) |
Provide a pointer to the search object. | |
KdTreePtr | getSearchMethod () const |
Get a pointer to the search method used. | |
double | getSearchParameter () const |
Get the internal search parameter. | |
void | setKSearch (int k) |
Set the number of k nearest neighbors to use for the feature estimation. | |
int | getKSearch () const |
get the number of k nearest neighbors used for the feature estimation. | |
void | setRadiusSearch (double radius) |
Set the sphere radius that is to be used for determining the nearest neighbors used for the feature estimation. | |
double | getRadiusSearch () const |
Get the sphere radius used for determining the neighbors. | |
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 () | |
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PCLBase () | |
Empty constructor. | |
PCLBase (const PCLBase &base) | |
Copy constructor. | |
virtual | ~PCLBase ()=default |
Destructor. | |
virtual void | setInputCloud (const PointCloudConstPtr &cloud) |
Provide a pointer to the input dataset. | |
PointCloudConstPtr const | getInputCloud () const |
Get a pointer to the input point cloud dataset. | |
virtual void | setIndices (const IndicesPtr &indices) |
Provide a pointer to the vector of indices that represents the input data. | |
virtual void | setIndices (const IndicesConstPtr &indices) |
Provide a pointer to the vector of indices that represents the input data. | |
virtual void | setIndices (const PointIndicesConstPtr &indices) |
Provide a pointer to the vector of indices that represents the input data. | |
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. | |
IndicesPtr | getIndices () |
Get a pointer to the vector of indices used. | |
IndicesConstPtr const | getIndices () const |
Get a pointer to the vector of indices used. | |
const PointInT & | operator[] (std::size_t pos) const |
Override PointCloud operator[] to shorten code. | |
Protected Member Functions | |
void | computeFeature (PointCloudOut &output) override |
Computes the normal for the complete cloud. | |
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const std::string & | getClassName () const |
Get a string representation of the name of this class. | |
virtual bool | initCompute () |
This method should get called before starting the actual computation. | |
virtual bool | deinitCompute () |
This method should get called after ending the actual computation. | |
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. | |
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. | |
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bool | initCompute () |
This method should get called before starting the actual computation. | |
bool | deinitCompute () |
This method should get called after finishing the actual computation. | |
Additional Inherited Members | |
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std::string | feature_name_ |
The feature name. | |
SearchMethodSurface | search_method_surface_ |
The search method template for points. | |
PointCloudInConstPtr | surface_ |
An input point cloud describing the surface that is to be used for nearest neighbors estimation. | |
KdTreePtr | tree_ |
A pointer to the spatial search object. | |
double | search_parameter_ |
The actual search parameter (from either search_radius_ or k_). | |
double | search_radius_ |
The nearest neighbors search radius for each point. | |
int | k_ |
The number of K nearest neighbors to use for each point. | |
bool | fake_surface_ |
If no surface is given, we use the input PointCloud as the surface. | |
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PointCloudConstPtr | input_ |
The input point cloud dataset. | |
IndicesPtr | indices_ |
A pointer to the vector of point indices to use. | |
bool | use_indices_ |
Set to true if point indices are used. | |
bool | fake_indices_ |
If no set of indices are given, we construct a set of fake indices that mimic the input PointCloud. | |
Surface normal estimation on dense data using a least-squares estimation based on a first-order Taylor approximation.
Definition at line 49 of file linear_least_squares_normal.h.
using pcl::LinearLeastSquaresNormalEstimation< PointInT, PointOutT >::ConstPtr = shared_ptr<const LinearLeastSquaresNormalEstimation<PointInT, PointOutT> > |
Definition at line 53 of file linear_least_squares_normal.h.
using pcl::LinearLeastSquaresNormalEstimation< PointInT, PointOutT >::PointCloudIn = typename Feature<PointInT, PointOutT>::PointCloudIn |
Definition at line 54 of file linear_least_squares_normal.h.
using pcl::LinearLeastSquaresNormalEstimation< PointInT, PointOutT >::PointCloudOut = typename Feature<PointInT, PointOutT>::PointCloudOut |
Definition at line 55 of file linear_least_squares_normal.h.
using pcl::LinearLeastSquaresNormalEstimation< PointInT, PointOutT >::Ptr = shared_ptr<LinearLeastSquaresNormalEstimation<PointInT, PointOutT> > |
Definition at line 52 of file linear_least_squares_normal.h.
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inline |
Constructor.
Definition at line 62 of file linear_least_squares_normal.h.
References pcl::Feature< PointInT, PointOutT >::feature_name_, pcl::Feature< PointInT, PointOutT >::k_, and pcl::Feature< PointInT, PointOutT >::tree_.
pcl::LinearLeastSquaresNormalEstimation< PointInT, PointOutT >::~LinearLeastSquaresNormalEstimation | ( | ) |
Destructor.
Definition at line 47 of file linear_least_squares_normal.hpp.
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overrideprotectedvirtual |
Computes the normal for the complete cloud.
[out] | output | the resultant normals |
Implements pcl::Feature< PointInT, PointOutT >.
Definition at line 155 of file linear_least_squares_normal.hpp.
void pcl::LinearLeastSquaresNormalEstimation< PointInT, PointOutT >::computePointNormal | ( | const int | pos_x, |
const int | pos_y, | ||
PointOutT & | normal ) |
Computes the normal at the specified position.
[in] | pos_x | x position (pixel) |
[in] | pos_y | y position (pixel) |
[out] | normal | the output estimated normal |
Definition at line 53 of file linear_least_squares_normal.hpp.
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inline |
Set whether to use depth depending smoothing or not.
[in] | use_depth_dependent_smoothing | decides whether the smoothing is depth dependent |
Definition at line 97 of file linear_least_squares_normal.h.
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inlineoverride |
Provide a pointer to the input dataset (overwrites the PCLBase::setInputCloud method)
[in] | cloud | the const boost shared pointer to a PointCloud message |
Definition at line 116 of file linear_least_squares_normal.h.
References pcl::PCLBase< PointInT >::input_.
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inline |
The depth change threshold for computing object borders.
[in] | max_depth_change_factor | the depth change threshold for computing object borders based on depth changes |
Definition at line 107 of file linear_least_squares_normal.h.
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inline |
Set the normal smoothing size.
[in] | normal_smoothing_size | factor which influences the size of the area used to smooth normals (depth dependent if useDepthDependentSmoothing is true) |
Definition at line 88 of file linear_least_squares_normal.h.