Point Cloud Library (PCL)  1.14.1-dev
List of all members | Classes | Public Types | Public Member Functions | Protected Member Functions
pcl::SampleConsensusModelTorus< PointT, PointNT > Class Template Reference

SampleConsensusModelTorus defines a model for 3D torus segmentation. More...

#include <pcl/sample_consensus/sac_model_torus.h>

+ Inheritance diagram for pcl::SampleConsensusModelTorus< PointT, PointNT >:
+ Collaboration diagram for pcl::SampleConsensusModelTorus< PointT, PointNT >:

Public Types

using Ptr = shared_ptr< SampleConsensusModelTorus< PointT, PointNT > >
 
using ConstPtr = shared_ptr< const SampleConsensusModelTorus< PointT, PointNT > >
 
- Public Types inherited from pcl::SampleConsensusModel< PointT >
using PointCloud = pcl::PointCloud< PointT >
 
using PointCloudConstPtr = typename PointCloud::ConstPtr
 
using PointCloudPtr = typename PointCloud::Ptr
 
using SearchPtr = typename pcl::search::Search< PointT >::Ptr
 
using Ptr = shared_ptr< SampleConsensusModel< PointT > >
 
using ConstPtr = shared_ptr< const SampleConsensusModel< PointT > >
 
- Public Types inherited from pcl::SampleConsensusModelFromNormals< PointT, PointNT >
using PointCloudNConstPtr = typename pcl::PointCloud< PointNT >::ConstPtr
 
using PointCloudNPtr = typename pcl::PointCloud< PointNT >::Ptr
 
using Ptr = shared_ptr< SampleConsensusModelFromNormals< PointT, PointNT > >
 
using ConstPtr = shared_ptr< const SampleConsensusModelFromNormals< PointT, PointNT > >
 

Public Member Functions

 SampleConsensusModelTorus (const PointCloudConstPtr &cloud, bool random=false)
 Constructor for base SampleConsensusModelTorus. More...
 
 SampleConsensusModelTorus (const PointCloudConstPtr &cloud, const Indices &indices, bool random=false)
 Constructor for base SampleConsensusModelTorus. More...
 
 SampleConsensusModelTorus (const SampleConsensusModelTorus &source)
 Copy constructor. More...
 
 ~SampleConsensusModelTorus () override=default
 Empty destructor. More...
 
SampleConsensusModelTorusoperator= (const SampleConsensusModelTorus &source)
 Copy constructor. More...
 
bool computeModelCoefficients (const Indices &samples, Eigen::VectorXf &model_coefficients) const override
 Check whether the given index samples can form a valid torus model, compute the model coefficients from these samples and store them in model_coefficients. More...
 
void getDistancesToModel (const Eigen::VectorXf &model_coefficients, std::vector< double > &distances) const override
 Compute all distances from the cloud data to a given torus model. More...
 
void selectWithinDistance (const Eigen::VectorXf &model_coefficients, const double threshold, Indices &inliers) override
 Select all the points which respect the given model coefficients as inliers. More...
 
std::size_t countWithinDistance (const Eigen::VectorXf &model_coefficients, const double threshold) const override
 Count all the points which respect the given model coefficients as inliers. More...
 
void optimizeModelCoefficients (const Indices &inliers, const Eigen::VectorXf &model_coefficients, Eigen::VectorXf &optimized_coefficients) const override
 Recompute the torus coefficients using the given inlier set and return them to the user. More...
 
void projectPoints (const Indices &inliers, const Eigen::VectorXf &model_coefficients, PointCloud &projected_points, bool copy_data_fields=true) const override
 Create a new point cloud with inliers projected onto the torus model. More...
 
bool doSamplesVerifyModel (const std::set< index_t > &indices, const Eigen::VectorXf &model_coefficients, const double threshold) const override
 Verify whether a subset of indices verifies the given torus model coefficients. More...
 
pcl::SacModel getModelType () const override
 Return a unique id for this model (SACMODEL_TORUS). More...
 
- Public Member Functions inherited from pcl::SampleConsensusModel< PointT >
 SampleConsensusModel (const PointCloudConstPtr &cloud, bool random=false)
 Constructor for base SampleConsensusModel. More...
 
 SampleConsensusModel (const PointCloudConstPtr &cloud, const Indices &indices, bool random=false)
 Constructor for base SampleConsensusModel. More...
 
virtual ~SampleConsensusModel ()=default
 Destructor for base SampleConsensusModel. More...
 
virtual void getSamples (int &iterations, Indices &samples)
 Get a set of random data samples and return them as point indices. More...
 
virtual void setInputCloud (const PointCloudConstPtr &cloud)
 Provide a pointer to the input dataset. More...
 
PointCloudConstPtr getInputCloud () const
 Get a pointer to the input point cloud dataset. More...
 
void setIndices (const IndicesPtr &indices)
 Provide a pointer to the vector of indices that represents the input data. More...
 
void setIndices (const Indices &indices)
 Provide the vector of indices that represents the input data. More...
 
IndicesPtr getIndices () const
 Get a pointer to the vector of indices used. More...
 
const std::string & getClassName () const
 Get a string representation of the name of this class. More...
 
unsigned int getSampleSize () const
 Return the size of a sample from which the model is computed. More...
 
unsigned int getModelSize () const
 Return the number of coefficients in the model. 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) const
 Get the minimum and maximum allowable radius limits for the model as set by the user. More...
 
void setModelConstraints (std::function< bool(const Eigen::VectorXf &)> function)
 This can be used to impose any kind of constraint on the model, e.g. More...
 
void setSamplesMaxDist (const double &radius, SearchPtr search)
 Set the maximum distance allowed when drawing random samples. More...
 
void getSamplesMaxDist (double &radius) const
 Get maximum distance allowed when drawing random samples. More...
 
double computeVariance (const std::vector< double > &error_sqr_dists) const
 Compute the variance of the errors to the model. More...
 
double computeVariance () const
 Compute the variance of the errors to the model from the internally estimated vector of distances. More...
 
- Public Member Functions inherited from pcl::SampleConsensusModelFromNormals< PointT, PointNT >
 SampleConsensusModelFromNormals ()
 Empty constructor for base SampleConsensusModelFromNormals. More...
 
virtual ~SampleConsensusModelFromNormals ()=default
 Destructor. More...
 
void setNormalDistanceWeight (const double w)
 Set the normal angular distance weight. More...
 
double getNormalDistanceWeight () const
 Get the normal angular distance weight. 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...
 

Protected Member Functions

void projectPointToTorus (const Eigen::Vector3f &pt, const Eigen::Vector3f &pt_n, const Eigen::VectorXf &model_coefficients, Eigen::Vector3f &pt_proj) const
 Project a point onto a torus given by its model coefficients (radii, torus_center_point, torus_normal) More...
 
bool isModelValid (const Eigen::VectorXf &model_coefficients) const override
 Check whether a model is valid given the user constraints. More...
 
bool isSampleGood (const Indices &samples) const override
 Check if a sample of indices results in a good sample of points indices. More...
 
- Protected Member Functions inherited from pcl::SampleConsensusModel< PointT >
 SampleConsensusModel (bool random=false)
 Empty constructor for base SampleConsensusModel. More...
 
void drawIndexSample (Indices &sample)
 Fills a sample array with random samples from the indices_ vector. More...
 
void drawIndexSampleRadius (Indices &sample)
 Fills a sample array with one random sample from the indices_ vector and other random samples that are closer than samples_radius_. More...
 
int rnd ()
 Boost-based random number generator. More...
 

Additional Inherited Members

- Protected Attributes inherited from pcl::SampleConsensusModel< PointT >
std::string model_name_
 The model name. More...
 
PointCloudConstPtr input_
 A boost shared pointer to the point cloud data array. More...
 
IndicesPtr indices_
 A pointer to the vector of point indices to use. 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...
 
Indices shuffled_indices_
 Data containing a shuffled version of the indices. More...
 
boost::mt19937 rng_alg_
 Boost-based random number generator algorithm. More...
 
std::shared_ptr< boost::uniform_int<> > rng_dist_
 Boost-based random number generator distribution. More...
 
std::shared_ptr< boost::variate_generator< boost::mt19937 &, boost::uniform_int<> > > rng_gen_
 Boost-based random number generator. More...
 
std::vector< double > error_sqr_dists_
 A vector holding the distances to the computed model. More...
 
unsigned int sample_size_
 The size of a sample from which the model is computed. More...
 
unsigned int model_size_
 The number of coefficients in the model. More...
 
std::function< bool(const Eigen::VectorXf &)> custom_model_constraints_
 A user defined function that takes model coefficients and returns whether the model is acceptable or not. More...
 
- Protected Attributes inherited from pcl::SampleConsensusModelFromNormals< PointT, PointNT >
double normal_distance_weight_ {0.0}
 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...
 
PointCloudNConstPtr normals_
 A pointer to the input dataset that contains the point normals of the XYZ dataset. More...
 
- Static Protected Attributes inherited from pcl::SampleConsensusModel< PointT >
static const unsigned int max_sample_checks_ = 1000
 The maximum number of samples to try until we get a good one. More...
 

Detailed Description

template<typename PointT, typename PointNT>
class pcl::SampleConsensusModelTorus< PointT, PointNT >

SampleConsensusModelTorus defines a model for 3D torus segmentation.

The model coefficients are defined as:

Author
lasdasdas

Definition at line 64 of file sac_model_torus.h.

Member Typedef Documentation

◆ ConstPtr

template<typename PointT , typename PointNT >
using pcl::SampleConsensusModelTorus< PointT, PointNT >::ConstPtr = shared_ptr<const SampleConsensusModelTorus<PointT, PointNT> >

Definition at line 82 of file sac_model_torus.h.

◆ Ptr

template<typename PointT , typename PointNT >
using pcl::SampleConsensusModelTorus< PointT, PointNT >::Ptr = shared_ptr<SampleConsensusModelTorus<PointT, PointNT> >

Definition at line 81 of file sac_model_torus.h.

Constructor & Destructor Documentation

◆ SampleConsensusModelTorus() [1/3]

template<typename PointT , typename PointNT >
pcl::SampleConsensusModelTorus< PointT, PointNT >::SampleConsensusModelTorus ( const PointCloudConstPtr cloud,
bool  random = false 
)
inline

Constructor for base SampleConsensusModelTorus.

Parameters
[in]cloudthe input point cloud dataset
[in]randomif true set the random seed to the current time, else set to 12345 (default: false)

Definition at line 89 of file sac_model_torus.h.

References pcl::SampleConsensusModel< PointT >::model_name_, pcl::SampleConsensusModel< PointT >::model_size_, and pcl::SampleConsensusModel< PointT >::sample_size_.

◆ SampleConsensusModelTorus() [2/3]

template<typename PointT , typename PointNT >
pcl::SampleConsensusModelTorus< PointT, PointNT >::SampleConsensusModelTorus ( const PointCloudConstPtr cloud,
const Indices indices,
bool  random = false 
)
inline

Constructor for base SampleConsensusModelTorus.

Parameters
[in]cloudthe input point cloud dataset
[in]indicesa vector of point indices to be used from cloud
[in]randomif true set the random seed to the current time, else set to 12345 (default: false)

Definition at line 104 of file sac_model_torus.h.

References pcl::SampleConsensusModel< PointT >::model_name_, pcl::SampleConsensusModel< PointT >::model_size_, and pcl::SampleConsensusModel< PointT >::sample_size_.

◆ SampleConsensusModelTorus() [3/3]

template<typename PointT , typename PointNT >
pcl::SampleConsensusModelTorus< PointT, PointNT >::SampleConsensusModelTorus ( const SampleConsensusModelTorus< PointT, PointNT > &  source)
inline

Copy constructor.

Parameters
[in]sourcethe model to copy into this

Definition at line 118 of file sac_model_torus.h.

References pcl::SampleConsensusModel< PointT >::model_name_.

◆ ~SampleConsensusModelTorus()

template<typename PointT , typename PointNT >
pcl::SampleConsensusModelTorus< PointT, PointNT >::~SampleConsensusModelTorus ( )
overridedefault

Empty destructor.

Member Function Documentation

◆ computeModelCoefficients()

template<typename PointT , typename PointNT >
bool pcl::SampleConsensusModelTorus< PointT, PointNT >::computeModelCoefficients ( const Indices samples,
Eigen::VectorXf &  model_coefficients 
) const
overridevirtual

Check whether the given index samples can form a valid torus model, compute the model coefficients from these samples and store them in model_coefficients.

The torus coefficients are: radii, torus_center_point, torus_normal.

Parameters
[in]samplesthe point indices found as possible good candidates for creating a valid model
[out]model_coefficientsthe resultant model coefficients

Implements pcl::SampleConsensusModel< PointT >.

Definition at line 97 of file sac_model_torus.hpp.

◆ countWithinDistance()

template<typename PointT , typename PointNT >
std::size_t pcl::SampleConsensusModelTorus< PointT, PointNT >::countWithinDistance ( const Eigen::VectorXf &  model_coefficients,
const double  threshold 
) const
overridevirtual

Count all the points which respect the given model coefficients as inliers.

Parameters
[in]model_coefficientsthe coefficients of a model that we need to compute distances to
[in]thresholdmaximum admissible distance threshold for determining the inliers from the outliers
Returns
the resultant number of inliers

Implements pcl::SampleConsensusModel< PointT >.

Definition at line 332 of file sac_model_torus.hpp.

References pcl::geometry::distance().

◆ doSamplesVerifyModel()

template<typename PointT , typename PointNT >
bool pcl::SampleConsensusModelTorus< PointT, PointNT >::doSamplesVerifyModel ( const std::set< index_t > &  indices,
const Eigen::VectorXf &  model_coefficients,
const double  threshold 
) const
overridevirtual

Verify whether a subset of indices verifies the given torus model coefficients.

Parameters
[in]indicesthe data indices that need to be tested against the torus model
[in]model_coefficientsthe torus model coefficients
[in]thresholda maximum admissible distance threshold for determining the inliers from the outliers

Implements pcl::SampleConsensusModel< PointT >.

Definition at line 529 of file sac_model_torus.hpp.

◆ getDistancesToModel()

template<typename PointT , typename PointNT >
void pcl::SampleConsensusModelTorus< PointT, PointNT >::getDistancesToModel ( const Eigen::VectorXf &  model_coefficients,
std::vector< double > &  distances 
) const
overridevirtual

Compute all distances from the cloud data to a given torus model.

Parameters
[in]model_coefficientsthe coefficients of a torus model that we need to compute distances to
[out]distancesthe resultant estimated distances

Implements pcl::SampleConsensusModel< PointT >.

Definition at line 271 of file sac_model_torus.hpp.

◆ getModelType()

template<typename PointT , typename PointNT >
pcl::SacModel pcl::SampleConsensusModelTorus< PointT, PointNT >::getModelType ( ) const
inlineoverridevirtual

Return a unique id for this model (SACMODEL_TORUS).

Implements pcl::SampleConsensusModel< PointT >.

Definition at line 215 of file sac_model_torus.h.

References pcl::SACMODEL_TORUS.

◆ isModelValid()

template<typename PointT , typename PointNT >
bool pcl::SampleConsensusModelTorus< PointT, PointNT >::isModelValid ( const Eigen::VectorXf &  model_coefficients) const
overrideprotectedvirtual

Check whether a model is valid given the user constraints.

Parameters
[in]model_coefficientsthe set of model coefficients

Reimplemented from pcl::SampleConsensusModel< PointT >.

Definition at line 549 of file sac_model_torus.hpp.

◆ isSampleGood()

template<typename PointT , typename PointNT >
bool pcl::SampleConsensusModelTorus< PointT, PointNT >::isSampleGood ( const Indices samples) const
overrideprotectedvirtual

Check if a sample of indices results in a good sample of points indices.

Pure virtual.

Parameters
[in]samplesthe resultant index samples

Implements pcl::SampleConsensusModel< PointT >.

Definition at line 53 of file sac_model_torus.hpp.

◆ operator=()

template<typename PointT , typename PointNT >
SampleConsensusModelTorus& pcl::SampleConsensusModelTorus< PointT, PointNT >::operator= ( const SampleConsensusModelTorus< PointT, PointNT > &  source)
inline

Copy constructor.

Parameters
[in]sourcethe model to copy into this

Definition at line 132 of file sac_model_torus.h.

◆ optimizeModelCoefficients()

template<typename PointT , typename PointNT >
void pcl::SampleConsensusModelTorus< PointT, PointNT >::optimizeModelCoefficients ( const Indices inliers,
const Eigen::VectorXf &  model_coefficients,
Eigen::VectorXf &  optimized_coefficients 
) const
overridevirtual

Recompute the torus coefficients using the given inlier set and return them to the user.

Parameters
[in]inliersthe data inliers found as supporting the model
[in]model_coefficientsthe initial guess for the optimization
[out]optimized_coefficientsthe resultant recomputed coefficients after non-linear optimization

Implements pcl::SampleConsensusModel< PointT >.

Definition at line 359 of file sac_model_torus.hpp.

◆ projectPoints()

template<typename PointT , typename PointNT >
void pcl::SampleConsensusModelTorus< PointT, PointNT >::projectPoints ( const Indices inliers,
const Eigen::VectorXf &  model_coefficients,
PointCloud projected_points,
bool  copy_data_fields = true 
) const
overridevirtual

Create a new point cloud with inliers projected onto the torus model.

Parameters
[in]inliersthe data inliers that we want to project on the torus model
[in]model_coefficientsthe coefficients of a torus model
[out]projected_pointsthe resultant projected points
[in]copy_data_fieldsset to true if we need to copy the other data fields

Implements pcl::SampleConsensusModel< PointT >.

Definition at line 466 of file sac_model_torus.hpp.

References pcl::PointCloud< PointT >::height, pcl::PointCloud< PointT >::resize(), and pcl::PointCloud< PointT >::width.

◆ projectPointToTorus()

template<typename PointT , typename PointNT >
void pcl::SampleConsensusModelTorus< PointT, PointNT >::projectPointToTorus ( const Eigen::Vector3f &  pt,
const Eigen::Vector3f &  pt_n,
const Eigen::VectorXf &  model_coefficients,
Eigen::Vector3f &  pt_proj 
) const
protected

Project a point onto a torus given by its model coefficients (radii, torus_center_point, torus_normal)

Parameters
[in]ptthe input point to project
[in]model_coefficientsthe coefficients of the torus (radii, torus_center_point, torus_normal)
[out]pt_projthe resultant projected point

Definition at line 407 of file sac_model_torus.hpp.

◆ selectWithinDistance()

template<typename PointT , typename PointNT >
void pcl::SampleConsensusModelTorus< PointT, PointNT >::selectWithinDistance ( const Eigen::VectorXf &  model_coefficients,
const double  threshold,
Indices inliers 
)
overridevirtual

Select all the points which respect the given model coefficients as inliers.

Parameters
[in]model_coefficientsthe coefficients of a torus model that we need to compute distances to
[in]thresholda maximum admissible distance threshold for determining the inliers from the outliers
[out]inliersthe resultant model inliers

Implements pcl::SampleConsensusModel< PointT >.

Definition at line 298 of file sac_model_torus.hpp.

References pcl::geometry::distance().


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