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SACSegmentationFromNormals represents the PCL nodelet segmentation class for Sample Consensus methods and models that require the use of surface normals for estimation. More...

#include <pcl/segmentation/sac_segmentation.h>

Public Types

using PointCloud = typename SACSegmentation< PointT >::PointCloud
using PointCloudPtr = typename PointCloud::Ptr
using PointCloudConstPtr = typename PointCloud::ConstPtr
using PointCloudN = pcl::PointCloud< PointNT >
using PointCloudNPtr = typename PointCloudN::Ptr
using PointCloudNConstPtr = typename PointCloudN::ConstPtr
using SampleConsensusPtr = typename SampleConsensus< PointT >::Ptr
using SampleConsensusModelPtr = typename SampleConsensusModel< PointT >::Ptr
using SampleConsensusModelFromNormalsPtr = typename SampleConsensusModelFromNormals< PointT, PointNT >::Ptr
- Public Types inherited from pcl::SACSegmentation< PointT >
using PointCloud = pcl::PointCloud< PointT >
using PointCloudPtr = typename PointCloud::Ptr
using PointCloudConstPtr = typename PointCloud::ConstPtr
using SearchPtr = typename pcl::search::Search< PointT >::Ptr
using SampleConsensusPtr = typename SampleConsensus< PointT >::Ptr
using SampleConsensusModelPtr = typename SampleConsensusModel< PointT >::Ptr
- 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

Public Member Functions

SACSegmentationFromNormals (bool random=false)
Empty constructor. More...
void setInputNormals (const PointCloudNConstPtr &normals)
Provide a pointer to the input dataset that contains the point normals of the XYZ dataset. More...
PointCloudNConstPtr getInputNormals () const
Get a pointer to the normals of the input XYZ point cloud dataset. More...
void setNormalDistanceWeight (double distance_weight)
Set the relative weight (between 0 and 1) to give to the angular distance (0 to pi/2) between point normals and the plane normal. More...
double getNormalDistanceWeight () const
Get the relative weight (between 0 and 1) to give to the angular distance (0 to pi/2) between point normals and the plane normal. More...
void setMinMaxOpeningAngle (const double &min_angle, const double &max_angle)
Set the minimum opning angle for a cone model. More...
void getMinMaxOpeningAngle (double &min_angle, double &max_angle)
Get the opening angle which we need minimum to validate a cone model. More...
void setDistanceFromOrigin (const double d)
Set the distance we expect a plane model to be from the origin. More...
double getDistanceFromOrigin () const
Get the distance of a plane model from the origin. More...
- Public Member Functions inherited from pcl::SACSegmentation< PointT >
SACSegmentation (bool random=false)
Empty constructor. More...
~SACSegmentation ()
Empty destructor. More...
void setModelType (int model)
The type of model to use (user given parameter). More...
int getModelType () const
Get the type of SAC model used. More...
SampleConsensusPtr getMethod () const
Get a pointer to the SAC method used. More...
SampleConsensusModelPtr getModel () const
Get a pointer to the SAC model used. More...
void setMethodType (int method)
The type of sample consensus method to use (user given parameter). More...
int getMethodType () const
Get the type of sample consensus method used. More...
void setDistanceThreshold (double threshold)
Distance to the model threshold (user given parameter). More...
double getDistanceThreshold () const
Get the distance to the model threshold. More...
void setMaxIterations (int max_iterations)
Set the maximum number of iterations before giving up. More...
int getMaxIterations () const
Get maximum number of iterations before giving up. More...
void setProbability (double probability)
Set the probability of choosing at least one sample free from outliers. More...
double getProbability () const
Get the probability of choosing at least one sample free from outliers. More...
void setNumberOfThreads (const int nr_threads=-1)
Set the number of threads to use or turn off parallelization. More...
void setOptimizeCoefficients (bool optimize)
Set to true if a coefficient refinement is required. More...
bool getOptimizeCoefficients () const
Get the coefficient refinement internal flag. More...
void setRadiusLimits (const double &min_radius, const double &max_radius)
Set the minimum and maximum allowable radius limits for the model (applicable to models that estimate a radius) More...
void getRadiusLimits (double &min_radius, double &max_radius)
Get the minimum and maximum allowable radius limits for the model as set by the user. More...
void setSamplesMaxDist (const double &radius, SearchPtr search)
Set the maximum distance allowed when drawing random samples. More...
void getSamplesMaxDist (double &radius)
Get maximum distance allowed when drawing random samples. More...
void setAxis (const Eigen::Vector3f &ax)
Set the axis along which we need to search for a model perpendicular to. More...
Eigen::Vector3f getAxis () const
Get the axis along which we need to search for a model perpendicular to. More...
void setEpsAngle (double ea)
Set the angle epsilon (delta) threshold. More...
double getEpsAngle () const
Get the epsilon (delta) model angle threshold in radians. More...
virtual void segment (PointIndices &inliers, ModelCoefficients &model_coefficients)
Base method for segmentation of a model in a PointCloud given by <setInputCloud (), setIndices ()> 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...
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 PointT & operator[] (std::size_t pos) const
Override PointCloud operator[] to shorten code. More...

Protected Member Functions

bool initSACModel (const int model_type) override
Initialize the Sample Consensus model and set its parameters. More...
std::string getClassName () const override
Class get name method. More...
- Protected Member Functions inherited from pcl::SACSegmentation< PointT >
virtual void initSAC (const int method_type)
Initialize the Sample Consensus method and set its parameters. 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...

Protected Attributes

PointCloudNConstPtr normals_
A pointer to the input dataset that contains the point normals of the XYZ dataset. More...
double distance_weight_
The relative weight (between 0 and 1) to give to the angular distance (0 to pi/2) between point normals and the plane normal. More...
double distance_from_origin_
The distance from the template plane to the origin. More...
double min_angle_
The minimum and maximum allowed opening angle of valid cone model. More...
double max_angle_
- Protected Attributes inherited from pcl::SACSegmentation< PointT >
SampleConsensusModelPtr model_
The model that needs to be segmented. More...
SampleConsensusPtr sac_
The sample consensus segmentation method. More...
int model_type_
The type of model to use (user given parameter). More...
int method_type_
The type of sample consensus method to use (user given parameter). More...
double threshold_
Distance to the model threshold (user given parameter). More...
bool optimize_coefficients_
Set to true if a coefficient refinement is required. More...
double radius_min_
The minimum and maximum radius limits for the model. More...
double radius_max_
double samples_radius_
The maximum distance of subsequent samples from the first (radius search) More...
SearchPtr samples_radius_search_
The search object for picking subsequent samples using radius search. More...
double eps_angle_
The maximum allowed difference between the model normal and the given axis. More...
Eigen::Vector3f axis_
The axis along which we need to search for a model perpendicular to. More...
int max_iterations_
Maximum number of iterations before giving up (user given parameter). More...
int threads_
The number of threads the scheduler should use, or a negative number if no parallelization is wanted. More...
double probability_
Desired probability of choosing at least one sample free from outliers (user given parameter). More...
bool random_
Set to true if we need a random seed. 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 PointT, typename PointNT>
class pcl::SACSegmentationFromNormals< PointT, PointNT >

SACSegmentationFromNormals represents the PCL nodelet segmentation class for Sample Consensus methods and models that require the use of surface normals for estimation.

Definition at line 321 of file sac_segmentation.h.

Member Typedef Documentation

PointCloud

template<typename PointT , typename PointNT >
using pcl::SACSegmentationFromNormals< PointT, PointNT >::PointCloud = typename SACSegmentation<PointT>::PointCloud

Definition at line 335 of file sac_segmentation.h.

PointCloudConstPtr

template<typename PointT , typename PointNT >
using pcl::SACSegmentationFromNormals< PointT, PointNT >::PointCloudConstPtr = typename PointCloud::ConstPtr

Definition at line 337 of file sac_segmentation.h.

PointCloudN

template<typename PointT , typename PointNT >
using pcl::SACSegmentationFromNormals< PointT, PointNT >::PointCloudN = pcl::PointCloud<PointNT>

Definition at line 339 of file sac_segmentation.h.

PointCloudNConstPtr

template<typename PointT , typename PointNT >
using pcl::SACSegmentationFromNormals< PointT, PointNT >::PointCloudNConstPtr = typename PointCloudN::ConstPtr

Definition at line 341 of file sac_segmentation.h.

PointCloudNPtr

template<typename PointT , typename PointNT >
using pcl::SACSegmentationFromNormals< PointT, PointNT >::PointCloudNPtr = typename PointCloudN::Ptr

Definition at line 340 of file sac_segmentation.h.

PointCloudPtr

template<typename PointT , typename PointNT >
using pcl::SACSegmentationFromNormals< PointT, PointNT >::PointCloudPtr = typename PointCloud::Ptr

Definition at line 336 of file sac_segmentation.h.

SampleConsensusModelFromNormalsPtr

template<typename PointT , typename PointNT >
using pcl::SACSegmentationFromNormals< PointT, PointNT >::SampleConsensusModelFromNormalsPtr = typename SampleConsensusModelFromNormals<PointT, PointNT>::Ptr

Definition at line 345 of file sac_segmentation.h.

SampleConsensusModelPtr

template<typename PointT , typename PointNT >
using pcl::SACSegmentationFromNormals< PointT, PointNT >::SampleConsensusModelPtr = typename SampleConsensusModel<PointT>::Ptr

Definition at line 344 of file sac_segmentation.h.

SampleConsensusPtr

template<typename PointT , typename PointNT >
using pcl::SACSegmentationFromNormals< PointT, PointNT >::SampleConsensusPtr = typename SampleConsensus<PointT>::Ptr

Definition at line 343 of file sac_segmentation.h.

Constructor & Destructor Documentation

SACSegmentationFromNormals()

template<typename PointT , typename PointNT >
pcl::SACSegmentationFromNormals< PointT, PointNT >::SACSegmentationFromNormals ( bool random = false )
inline

Empty constructor.

Parameters
[in] random if true set the random seed to the current time, else set to 12345 (default: false)

Definition at line 350 of file sac_segmentation.h.

Member Function Documentation

getClassName()

template<typename PointT , typename PointNT >
std::string pcl::SACSegmentationFromNormals< PointT, PointNT >::getClassName ( ) const
inlineoverrideprotectedvirtual

Class get name method.

Reimplemented from pcl::SACSegmentation< PointT >.

Definition at line 435 of file sac_segmentation.h.

getDistanceFromOrigin()

template<typename PointT , typename PointNT >
double pcl::SACSegmentationFromNormals< PointT, PointNT >::getDistanceFromOrigin ( ) const
inline

Get the distance of a plane model from the origin.

Definition at line 409 of file sac_segmentation.h.

References pcl::SACSegmentationFromNormals< PointT, PointNT >::distance_from_origin_.

getInputNormals()

template<typename PointT , typename PointNT >
PointCloudNConstPtr pcl::SACSegmentationFromNormals< PointT, PointNT >::getInputNormals ( ) const
inline

Get a pointer to the normals of the input XYZ point cloud dataset.

Definition at line 368 of file sac_segmentation.h.

References pcl::SACSegmentationFromNormals< PointT, PointNT >::normals_.

getMinMaxOpeningAngle()

template<typename PointT , typename PointNT >
void pcl::SACSegmentationFromNormals< PointT, PointNT >::getMinMaxOpeningAngle ( double & min_angle,
double & max_angle
)
inline

Get the opening angle which we need minimum to validate a cone model.

Definition at line 395 of file sac_segmentation.h.

References pcl::SACSegmentationFromNormals< PointT, PointNT >::max_angle_, and pcl::SACSegmentationFromNormals< PointT, PointNT >::min_angle_.

getNormalDistanceWeight()

template<typename PointT , typename PointNT >
double pcl::SACSegmentationFromNormals< PointT, PointNT >::getNormalDistanceWeight ( ) const
inline

Get the relative weight (between 0 and 1) to give to the angular distance (0 to pi/2) between point normals and the plane normal.

Definition at line 380 of file sac_segmentation.h.

References pcl::SACSegmentationFromNormals< PointT, PointNT >::distance_weight_.

initSACModel()

template<typename PointT , typename PointNT >
bool pcl::SACSegmentationFromNormals< PointT, PointNT >::initSACModel ( const int model_type )
overrideprotectedvirtual

Initialize the Sample Consensus model and set its parameters.

Parameters
[in] model_type the type of SAC model that is to be used

Reimplemented from pcl::SACSegmentation< PointT >.

Definition at line 349 of file sac_segmentation.hpp.

References pcl::SampleConsensusModelNormalParallelPlane< PointT, PointNT >::getAxis(), pcl::SampleConsensusModelCylinder< PointT, PointNT >::getAxis(), pcl::SampleConsensusModelCone< PointT, PointNT >::getAxis(), pcl::SampleConsensusModelNormalParallelPlane< PointT, PointNT >::getDistanceFromOrigin(), pcl::SampleConsensusModelCylinder< PointT, PointNT >::getEpsAngle(), pcl::SampleConsensusModelCone< PointT, PointNT >::getEpsAngle(), pcl::SampleConsensusModelNormalParallelPlane< PointT, PointNT >::getEpsAngle(), pcl::SampleConsensusModelCone< PointT, PointNT >::getMinMaxOpeningAngle(), pcl::SampleConsensusModelFromNormals< PointT, PointNT >::getNormalDistanceWeight(), pcl::SampleConsensusModel< PointT >::getRadiusLimits(), M_PI, pcl::SACMODEL_CONE, pcl::SACMODEL_CYLINDER, pcl::SACMODEL_NORMAL_PARALLEL_PLANE, pcl::SACMODEL_NORMAL_PLANE, pcl::SACMODEL_NORMAL_SPHERE, pcl::SampleConsensusModelNormalParallelPlane< PointT, PointNT >::setAxis(), pcl::SampleConsensusModelCylinder< PointT, PointNT >::setAxis(), pcl::SampleConsensusModelCone< PointT, PointNT >::setAxis(), pcl::SampleConsensusModelNormalParallelPlane< PointT, PointNT >::setDistanceFromOrigin(), pcl::SampleConsensusModelCylinder< PointT, PointNT >::setEpsAngle(), pcl::SampleConsensusModelCone< PointT, PointNT >::setEpsAngle(), pcl::SampleConsensusModelNormalParallelPlane< PointT, PointNT >::setEpsAngle(), pcl::SampleConsensusModelFromNormals< PointT, PointNT >::setInputNormals(), pcl::SampleConsensusModelCone< PointT, PointNT >::setMinMaxOpeningAngle(), pcl::SampleConsensusModelFromNormals< PointT, PointNT >::setNormalDistanceWeight(), and pcl::SampleConsensusModel< PointT >::setRadiusLimits().

setDistanceFromOrigin()

template<typename PointT , typename PointNT >
void pcl::SACSegmentationFromNormals< PointT, PointNT >::setDistanceFromOrigin ( const double d )
inline

Set the distance we expect a plane model to be from the origin.

Parameters
[in] d distance from the template plane model to the origin

Definition at line 405 of file sac_segmentation.h.

References pcl::SACSegmentationFromNormals< PointT, PointNT >::distance_from_origin_.

setInputNormals()

template<typename PointT , typename PointNT >
void pcl::SACSegmentationFromNormals< PointT, PointNT >::setInputNormals ( const PointCloudNConstPtr & normals )
inline

Provide a pointer to the input dataset that contains the point normals of the XYZ dataset.

Parameters
[in] normals the const shared pointer to a PointCloud message

Definition at line 364 of file sac_segmentation.h.

References pcl::SACSegmentationFromNormals< PointT, PointNT >::normals_.

setMinMaxOpeningAngle()

template<typename PointT , typename PointNT >
void pcl::SACSegmentationFromNormals< PointT, PointNT >::setMinMaxOpeningAngle ( const double & min_angle,
const double & max_angle
)
inline

Set the minimum opning angle for a cone model.

Parameters
min_angle the opening angle which we need minimum to validate a cone model.
max_angle the opening angle which we need maximum to validate a cone model.

Definition at line 387 of file sac_segmentation.h.

References pcl::SACSegmentationFromNormals< PointT, PointNT >::max_angle_, and pcl::SACSegmentationFromNormals< PointT, PointNT >::min_angle_.

setNormalDistanceWeight()

template<typename PointT , typename PointNT >
void pcl::SACSegmentationFromNormals< PointT, PointNT >::setNormalDistanceWeight ( double distance_weight )
inline

Set the relative weight (between 0 and 1) to give to the angular distance (0 to pi/2) between point normals and the plane normal.

Parameters
[in] distance_weight the distance/angular weight

Definition at line 375 of file sac_segmentation.h.

References pcl::SACSegmentationFromNormals< PointT, PointNT >::distance_weight_.

Member Data Documentation

distance_from_origin_

template<typename PointT , typename PointNT >
double pcl::SACSegmentationFromNormals< PointT, PointNT >::distance_from_origin_
protected

distance_weight_

template<typename PointT , typename PointNT >
double pcl::SACSegmentationFromNormals< PointT, PointNT >::distance_weight_
protected

The relative weight (between 0 and 1) to give to the angular distance (0 to pi/2) between point normals and the plane normal.

Definition at line 418 of file sac_segmentation.h.

Referenced by pcl::SACSegmentationFromNormals< PointT, PointNT >::getNormalDistanceWeight(), and pcl::SACSegmentationFromNormals< PointT, PointNT >::setNormalDistanceWeight().

max_angle_

template<typename PointT , typename PointNT >
double pcl::SACSegmentationFromNormals< PointT, PointNT >::max_angle_
protected

min_angle_

template<typename PointT , typename PointNT >
double pcl::SACSegmentationFromNormals< PointT, PointNT >::min_angle_
protected

The minimum and maximum allowed opening angle of valid cone model.

Definition at line 424 of file sac_segmentation.h.

Referenced by pcl::SACSegmentationFromNormals< PointT, PointNT >::getMinMaxOpeningAngle(), and pcl::SACSegmentationFromNormals< PointT, PointNT >::setMinMaxOpeningAngle().

normals_

template<typename PointT , typename PointNT >
PointCloudNConstPtr pcl::SACSegmentationFromNormals< PointT, PointNT >::normals_
protected

A pointer to the input dataset that contains the point normals of the XYZ dataset.

Definition at line 413 of file sac_segmentation.h.

Referenced by pcl::SACSegmentationFromNormals< PointT, PointNT >::getInputNormals(), and pcl::SACSegmentationFromNormals< PointT, PointNT >::setInputNormals().


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_s_a_c_segmentation_from_normals.html