Point Cloud Library (PCL) 1.12.0
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pcl::SampleConsensusModelCone< PointT, PointNT > Class Template Reference

SampleConsensusModelCone defines a model for 3D cone segmentation. More...

#include <pcl/sample_consensus/sac_model_cone.h>

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

Public Types

using PointCloud = typename SampleConsensusModel< PointT >::PointCloud
 
using PointCloudPtr = typename SampleConsensusModel< PointT >::PointCloudPtr
 
using PointCloudConstPtr = typename SampleConsensusModel< PointT >::PointCloudConstPtr
 
using Ptr = shared_ptr< SampleConsensusModelCone< PointT, PointNT > >
 
using ConstPtr = shared_ptr< const SampleConsensusModelCone< 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

 SampleConsensusModelCone (const PointCloudConstPtr &cloud, bool random=false)
 Constructor for base SampleConsensusModelCone.
 
 SampleConsensusModelCone (const PointCloudConstPtr &cloud, const Indices &indices, bool random=false)
 Constructor for base SampleConsensusModelCone.
 
 SampleConsensusModelCone (const SampleConsensusModelCone &source)
 Copy constructor.
 
 ~SampleConsensusModelCone ()
 Empty destructor.
 
SampleConsensusModelConeoperator= (const SampleConsensusModelCone &source)
 Copy constructor.
 
void setEpsAngle (double ea)
 Set the angle epsilon (delta) threshold.
 
double getEpsAngle () const
 Get the angle epsilon (delta) threshold.
 
void setAxis (const Eigen::Vector3f &ax)
 Set the axis along which we need to search for a cone direction.
 
Eigen::Vector3f getAxis () const
 Get the axis along which we need to search for a cone direction.
 
void setMinMaxOpeningAngle (const double &min_angle, const double &max_angle)
 Set the minimum and maximum allowable opening angle for a cone model given from a user.
 
void getMinMaxOpeningAngle (double &min_angle, double &max_angle) const
 Get the opening angle which we need minimum to validate a cone model.
 
bool computeModelCoefficients (const Indices &samples, Eigen::VectorXf &model_coefficients) const override
 Check whether the given index samples can form a valid cone model, compute the model coefficients from these samples and store them in model_coefficients.
 
void getDistancesToModel (const Eigen::VectorXf &model_coefficients, std::vector< double > &distances) const override
 Compute all distances from the cloud data to a given cone model.
 
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.
 
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.
 
void optimizeModelCoefficients (const Indices &inliers, const Eigen::VectorXf &model_coefficients, Eigen::VectorXf &optimized_coefficients) const override
 Recompute the cone coefficients using the given inlier set and return them to the user.
 
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 cone model.
 
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 cone model coefficients.
 
pcl::SacModel getModelType () const override
 Return a unique id for this model (SACMODEL_CONE).
 
- Public Member Functions inherited from pcl::SampleConsensusModel< PointT >
 SampleConsensusModel (const PointCloudConstPtr &cloud, bool random=false)
 Constructor for base SampleConsensusModel.
 
 SampleConsensusModel (const PointCloudConstPtr &cloud, const Indices &indices, bool random=false)
 Constructor for base SampleConsensusModel.
 
virtual ~SampleConsensusModel ()
 Destructor for base SampleConsensusModel.
 
virtual void getSamples (int &iterations, Indices &samples)
 Get a set of random data samples and return them as point indices.
 
virtual void setInputCloud (const PointCloudConstPtr &cloud)
 Provide a pointer to the input dataset.
 
PointCloudConstPtr getInputCloud () const
 Get a pointer to the input point cloud dataset.
 
void setIndices (const IndicesPtr &indices)
 Provide a pointer to the vector of indices that represents the input data.
 
void setIndices (const Indices &indices)
 Provide the vector of indices that represents the input data.
 
IndicesPtr getIndices () const
 Get a pointer to the vector of indices used.
 
const std::string & getClassName () const
 Get a string representation of the name of this class.
 
unsigned int getSampleSize () const
 Return the size of a sample from which the model is computed.
 
unsigned int getModelSize () const
 Return the number of coefficients in the model.
 
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)
 
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.
 
void setModelConstraints (std::function< bool(const Eigen::VectorXf &)> function)
 This can be used to impose any kind of constraint on the model, e.g.
 
void setSamplesMaxDist (const double &radius, SearchPtr search)
 Set the maximum distance allowed when drawing random samples.
 
void getSamplesMaxDist (double &radius) const
 Get maximum distance allowed when drawing random samples.
 
double computeVariance (const std::vector< double > &error_sqr_dists) const
 Compute the variance of the errors to the model.
 
double computeVariance () const
 Compute the variance of the errors to the model from the internally estimated vector of distances.
 
- Public Member Functions inherited from pcl::SampleConsensusModelFromNormals< PointT, PointNT >
 SampleConsensusModelFromNormals ()
 Empty constructor for base SampleConsensusModelFromNormals.
 
virtual ~SampleConsensusModelFromNormals ()
 Destructor.
 
void setNormalDistanceWeight (const double w)
 Set the normal angular distance weight.
 
double getNormalDistanceWeight () const
 Get the normal angular distance weight.
 
void setInputNormals (const PointCloudNConstPtr &normals)
 Provide a pointer to the input dataset that contains the point normals of the XYZ dataset.
 
PointCloudNConstPtr getInputNormals () const
 Get a pointer to the normals of the input XYZ point cloud dataset.
 

Protected Member Functions

double pointToAxisDistance (const Eigen::Vector4f &pt, const Eigen::VectorXf &model_coefficients) const
 Get the distance from a point to a line (represented by a point and a direction)
 
bool isModelValid (const Eigen::VectorXf &model_coefficients) const override
 Check whether a model is valid given the user constraints.
 
bool isSampleGood (const Indices &samples) const override
 Check if a sample of indices results in a good sample of points indices.
 
- Protected Member Functions inherited from pcl::SampleConsensusModel< PointT >
 SampleConsensusModel (bool random=false)
 Empty constructor for base SampleConsensusModel.
 
void drawIndexSample (Indices &sample)
 Fills a sample array with random samples from the indices_ vector.
 
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_.
 
int rnd ()
 Boost-based random number generator.
 

Additional Inherited Members

- Protected Attributes inherited from pcl::SampleConsensusModel< PointT >
std::string model_name_
 The model name.
 
PointCloudConstPtr input_
 A boost shared pointer to the point cloud data array.
 
IndicesPtr indices_
 A pointer to the vector of point indices to use.
 
double radius_min_
 The minimum and maximum radius limits for the model.
 
double radius_max_
 
double samples_radius_
 The maximum distance of subsequent samples from the first (radius search)
 
SearchPtr samples_radius_search_
 The search object for picking subsequent samples using radius search.
 
Indices shuffled_indices_
 Data containing a shuffled version of the indices.
 
boost::mt19937 rng_alg_
 Boost-based random number generator algorithm.
 
std::shared_ptr< boost::uniform_int<> > rng_dist_
 Boost-based random number generator distribution.
 
std::shared_ptr< boost::variate_generator< boost::mt19937 &, boost::uniform_int<> > > rng_gen_
 Boost-based random number generator.
 
std::vector< double > error_sqr_dists_
 A vector holding the distances to the computed model.
 
unsigned int sample_size_
 The size of a sample from which the model is computed.
 
unsigned int model_size_
 The number of coefficients in the model.
 
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.
 
- Protected Attributes inherited from pcl::SampleConsensusModelFromNormals< PointT, PointNT >
double normal_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.
 
PointCloudNConstPtr normals_
 A pointer to the input dataset that contains the point normals of the XYZ dataset.
 
- 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.
 

Detailed Description

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

SampleConsensusModelCone defines a model for 3D cone segmentation.

The model coefficients are defined as:

Author
Stefan Schrandt

Definition at line 62 of file sac_model_cone.h.

Member Typedef Documentation

◆ ConstPtr

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

Definition at line 79 of file sac_model_cone.h.

◆ PointCloud

template<typename PointT , typename PointNT >
using pcl::SampleConsensusModelCone< PointT, PointNT >::PointCloud = typename SampleConsensusModel<PointT>::PointCloud

Definition at line 74 of file sac_model_cone.h.

◆ PointCloudConstPtr

template<typename PointT , typename PointNT >
using pcl::SampleConsensusModelCone< PointT, PointNT >::PointCloudConstPtr = typename SampleConsensusModel<PointT>::PointCloudConstPtr

Definition at line 76 of file sac_model_cone.h.

◆ PointCloudPtr

template<typename PointT , typename PointNT >
using pcl::SampleConsensusModelCone< PointT, PointNT >::PointCloudPtr = typename SampleConsensusModel<PointT>::PointCloudPtr

Definition at line 75 of file sac_model_cone.h.

◆ Ptr

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

Definition at line 78 of file sac_model_cone.h.

Constructor & Destructor Documentation

◆ SampleConsensusModelCone() [1/3]

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

Constructor for base SampleConsensusModelCone.

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 85 of file sac_model_cone.h.

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

◆ SampleConsensusModelCone() [2/3]

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

Constructor for base SampleConsensusModelCone.

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 103 of file sac_model_cone.h.

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

◆ SampleConsensusModelCone() [3/3]

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

Copy constructor.

Parameters
[in]sourcethe model to copy into this

Definition at line 121 of file sac_model_cone.h.

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

◆ ~SampleConsensusModelCone()

template<typename PointT , typename PointNT >
pcl::SampleConsensusModelCone< PointT, PointNT >::~SampleConsensusModelCone ( )
inline

Empty destructor.

Definition at line 131 of file sac_model_cone.h.

Member Function Documentation

◆ computeModelCoefficients()

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

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

The cone coefficients are: apex, axis_direction, opening_angle.

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 61 of file sac_model_cone.hpp.

◆ countWithinDistance()

template<typename PointT , typename PointNT >
std::size_t pcl::SampleConsensusModelCone< 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 266 of file sac_model_cone.hpp.

◆ doSamplesVerifyModel()

template<typename PointT , typename PointNT >
bool pcl::SampleConsensusModelCone< 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 cone model coefficients.

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

Implements pcl::SampleConsensusModel< PointT >.

Definition at line 456 of file sac_model_cone.hpp.

◆ getAxis()

template<typename PointT , typename PointNT >
Eigen::Vector3f pcl::SampleConsensusModelCone< PointT, PointNT >::getAxis ( ) const
inline

Get the axis along which we need to search for a cone direction.

Definition at line 166 of file sac_model_cone.h.

Referenced by pcl::SACSegmentationFromNormals< PointT, PointNT >::initSACModel().

◆ getDistancesToModel()

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

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

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

Implements pcl::SampleConsensusModel< PointT >.

Definition at line 146 of file sac_model_cone.hpp.

References pcl::getAngle3D(), and M_PI.

◆ getEpsAngle()

template<typename PointT , typename PointNT >
double pcl::SampleConsensusModelCone< PointT, PointNT >::getEpsAngle ( ) const
inline

Get the angle epsilon (delta) threshold.

Definition at line 156 of file sac_model_cone.h.

Referenced by pcl::SACSegmentationFromNormals< PointT, PointNT >::initSACModel().

◆ getMinMaxOpeningAngle()

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

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

Parameters
[out]min_anglethe minimum allowable opening angle of a cone model
[out]max_anglethe maximum allowable opening angle of a cone model

Definition at line 185 of file sac_model_cone.h.

Referenced by pcl::SACSegmentationFromNormals< PointT, PointNT >::initSACModel().

◆ getModelType()

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

Return a unique id for this model (SACMODEL_CONE).

Implements pcl::SampleConsensusModel< PointT >.

Definition at line 266 of file sac_model_cone.h.

References pcl::SACMODEL_CONE.

◆ isModelValid()

template<typename PointT , typename PointNT >
bool pcl::SampleConsensusModelCone< 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 509 of file sac_model_cone.hpp.

References pcl::getAngle3D(), and M_PI.

◆ isSampleGood()

template<typename PointT , typename PointNT >
bool pcl::SampleConsensusModelCone< 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 49 of file sac_model_cone.hpp.

◆ operator=()

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

Copy constructor.

Parameters
[in]sourcethe model to copy into this

Definition at line 137 of file sac_model_cone.h.

◆ optimizeModelCoefficients()

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

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

Note
: these are the coefficients of the cone model after refinement (e.g. after SVD)
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 322 of file sac_model_cone.hpp.

◆ pointToAxisDistance()

template<typename PointT , typename PointNT >
double pcl::SampleConsensusModelCone< PointT, PointNT >::pointToAxisDistance ( const Eigen::Vector4f &  pt,
const Eigen::VectorXf &  model_coefficients 
) const
protected

Get the distance from a point to a line (represented by a point and a direction)

Parameters
[in]pta point
[in]model_coefficientsthe line coefficients (a point on the line, line direction)

Definition at line 499 of file sac_model_cone.hpp.

References pcl::sqrPointToLineDistance().

◆ projectPoints()

template<typename PointT , typename PointNT >
void pcl::SampleConsensusModelCone< 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 cone model.

Parameters
[in]inliersthe data inliers that we want to project on the cone model
[in]model_coefficientsthe coefficients of a cone 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 360 of file sac_model_cone.hpp.

◆ selectWithinDistance()

template<typename PointT , typename PointNT >
void pcl::SampleConsensusModelCone< 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 cone 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 200 of file sac_model_cone.hpp.

◆ setAxis()

template<typename PointT , typename PointNT >
void pcl::SampleConsensusModelCone< PointT, PointNT >::setAxis ( const Eigen::Vector3f &  ax)
inline

Set the axis along which we need to search for a cone direction.

Parameters
[in]axthe axis along which we need to search for a cone direction

Definition at line 162 of file sac_model_cone.h.

Referenced by pcl::SACSegmentationFromNormals< PointT, PointNT >::initSACModel().

◆ setEpsAngle()

template<typename PointT , typename PointNT >
void pcl::SampleConsensusModelCone< PointT, PointNT >::setEpsAngle ( double  ea)
inline

Set the angle epsilon (delta) threshold.

Parameters
[in]eathe maximum allowed difference between the cone's axis and the given axis.

Definition at line 152 of file sac_model_cone.h.

Referenced by pcl::SACSegmentationFromNormals< PointT, PointNT >::initSACModel().

◆ setMinMaxOpeningAngle()

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

Set the minimum and maximum allowable opening angle for a cone model given from a user.

Parameters
[in]min_anglethe minimum allowable opening angle of a cone model
[in]max_anglethe maximum allowable opening angle of a cone model

Definition at line 174 of file sac_model_cone.h.

Referenced by pcl::SACSegmentationFromNormals< PointT, PointNT >::initSACModel().


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