Point Cloud Library (PCL)  1.8.1-dev
List of all members | Public Types | Public Member Functions | Protected Member Functions | Protected Attributes | Static Protected Attributes | Friends
pcl::SampleConsensusModel< PointT > Class Template Referenceabstract

SampleConsensusModel represents the base model class. More...

#include <pcl/sample_consensus/sac_model.h>

+ Inheritance diagram for pcl::SampleConsensusModel< PointT >:

Public Types

typedef pcl::PointCloud< PointTPointCloud
 
typedef pcl::PointCloud
< PointT >::ConstPtr 
PointCloudConstPtr
 
typedef pcl::PointCloud
< PointT >::Ptr 
PointCloudPtr
 
typedef pcl::search::Search
< PointT >::Ptr 
SearchPtr
 
typedef boost::shared_ptr
< SampleConsensusModel
Ptr
 
typedef boost::shared_ptr
< const SampleConsensusModel
ConstPtr
 

Public Member Functions

 SampleConsensusModel (const PointCloudConstPtr &cloud, bool random=false)
 Constructor for base SampleConsensusModel. More...
 
 SampleConsensusModel (const PointCloudConstPtr &cloud, const std::vector< int > &indices, bool random=false)
 Constructor for base SampleConsensusModel. More...
 
virtual ~SampleConsensusModel ()
 Destructor for base SampleConsensusModel. More...
 
virtual void getSamples (int &iterations, std::vector< int > &samples)
 Get a set of random data samples and return them as point indices. More...
 
virtual bool computeModelCoefficients (const std::vector< int > &samples, Eigen::VectorXf &model_coefficients)=0
 Check whether the given index samples can form a valid model, compute the model coefficients from these samples and store them in model_coefficients. More...
 
virtual void optimizeModelCoefficients (const std::vector< int > &inliers, const Eigen::VectorXf &model_coefficients, Eigen::VectorXf &optimized_coefficients)=0
 Recompute the model coefficients using the given inlier set and return them to the user. More...
 
virtual void getDistancesToModel (const Eigen::VectorXf &model_coefficients, std::vector< double > &distances)=0
 Compute all distances from the cloud data to a given model. More...
 
virtual void selectWithinDistance (const Eigen::VectorXf &model_coefficients, const double threshold, std::vector< int > &inliers)=0
 Select all the points which respect the given model coefficients as inliers. More...
 
virtual int countWithinDistance (const Eigen::VectorXf &model_coefficients, const double threshold)=0
 Count all the points which respect the given model coefficients as inliers. More...
 
virtual void projectPoints (const std::vector< int > &inliers, const Eigen::VectorXf &model_coefficients, PointCloud &projected_points, bool copy_data_fields=true)=0
 Create a new point cloud with inliers projected onto the model. More...
 
virtual bool doSamplesVerifyModel (const std::set< int > &indices, const Eigen::VectorXf &model_coefficients, const double threshold)=0
 Verify whether a subset of indices verifies a given set of model coefficients. 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 boost::shared_ptr< std::vector< int > > &indices)
 Provide a pointer to the vector of indices that represents the input data. More...
 
void setIndices (const std::vector< int > &indices)
 Provide the vector of indices that represents the input data. More...
 
boost::shared_ptr< std::vector
< int > > 
getIndices () const
 Get a pointer to the vector of indices used. More...
 
virtual SacModel getModelType () const =0
 Return an unique id for each type of model employed. 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)
 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...
 
double computeVariance (const std::vector< double > &error_sqr_dists)
 Compute the variance of the errors to the model. More...
 
double computeVariance ()
 Compute the variance of the errors to the model from the internally estimated vector of distances. More...
 

Protected Member Functions

 SampleConsensusModel (bool random=false)
 Empty constructor for base SampleConsensusModel. More...
 
void drawIndexSample (std::vector< int > &sample)
 Fills a sample array with random samples from the indices_ vector. More...
 
void drawIndexSampleRadius (std::vector< int > &sample)
 Fills a sample array with one random sample from the indices_ vector and other random samples that are closer than samples_radius_. More...
 
virtual bool isModelValid (const Eigen::VectorXf &model_coefficients)
 Check whether a model is valid given the user constraints. More...
 
virtual bool isSampleGood (const std::vector< int > &samples) const =0
 Check if a sample of indices results in a good sample of points indices. More...
 
int rnd ()
 Boost-based random number generator. More...
 

Protected Attributes

std::string model_name_
 The model name. More...
 
PointCloudConstPtr input_
 A boost shared pointer to the point cloud data array. More...
 
boost::shared_ptr< std::vector
< int > > 
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...
 
std::vector< int > shuffled_indices_
 Data containing a shuffled version of the indices. More...
 
boost::mt19937 rng_alg_
 Boost-based random number generator algorithm. More...
 
boost::shared_ptr
< boost::uniform_int<> > 
rng_dist_
 Boost-based random number generator distribution. More...
 
boost::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...
 

Static Protected Attributes

static const unsigned int max_sample_checks_ = 1000
 The maximum number of samples to try until we get a good one. More...
 

Friends

class ProgressiveSampleConsensus< PointT >
 

Detailed Description

template<typename PointT>
class pcl::SampleConsensusModel< PointT >

SampleConsensusModel represents the base model class.

All sample consensus models must inherit from this class.

Author
Radu B. Rusu

Definition at line 66 of file sac_model.h.

Member Typedef Documentation

template<typename PointT>
typedef boost::shared_ptr<const SampleConsensusModel> pcl::SampleConsensusModel< PointT >::ConstPtr

Definition at line 75 of file sac_model.h.

template<typename PointT>
typedef pcl::PointCloud<PointT> pcl::SampleConsensusModel< PointT >::PointCloud

Definition at line 69 of file sac_model.h.

Definition at line 70 of file sac_model.h.

template<typename PointT>
typedef pcl::PointCloud<PointT>::Ptr pcl::SampleConsensusModel< PointT >::PointCloudPtr

Definition at line 71 of file sac_model.h.

template<typename PointT>
typedef boost::shared_ptr<SampleConsensusModel> pcl::SampleConsensusModel< PointT >::Ptr

Definition at line 74 of file sac_model.h.

template<typename PointT>
typedef pcl::search::Search<PointT>::Ptr pcl::SampleConsensusModel< PointT >::SearchPtr

Definition at line 72 of file sac_model.h.

Constructor & Destructor Documentation

template<typename PointT>
pcl::SampleConsensusModel< PointT >::SampleConsensusModel ( bool  random = false)
inlineprotected

Empty constructor for base SampleConsensusModel.

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

Definition at line 81 of file sac_model.h.

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

Constructor for base SampleConsensusModel.

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 108 of file sac_model.h.

template<typename PointT>
pcl::SampleConsensusModel< PointT >::SampleConsensusModel ( const PointCloudConstPtr cloud,
const std::vector< int > &  indices,
bool  random = false 
)
inline

Constructor for base SampleConsensusModel.

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 138 of file sac_model.h.

template<typename PointT>
virtual pcl::SampleConsensusModel< PointT >::~SampleConsensusModel ( )
inlinevirtual

Destructor for base SampleConsensusModel.

Definition at line 170 of file sac_model.h.

Member Function Documentation

template<typename PointT>
virtual bool pcl::SampleConsensusModel< PointT >::computeModelCoefficients ( const std::vector< int > &  samples,
Eigen::VectorXf &  model_coefficients 
)
pure virtual
template<typename PointT>
double pcl::SampleConsensusModel< PointT >::computeVariance ( const std::vector< double > &  error_sqr_dists)
inline

Compute the variance of the errors to the model.

Parameters
[in]error_sqr_distsa vector holding the distances

Definition at line 425 of file sac_model.h.

template<typename PointT>
double pcl::SampleConsensusModel< PointT >::computeVariance ( )
inline

Compute the variance of the errors to the model from the internally estimated vector of distances.

The model must be computed first (or at least selectWithinDistance must be called).

Definition at line 439 of file sac_model.h.

Referenced by pcl::SampleConsensusModel< WeightSACPointType >::computeVariance().

template<typename PointT>
virtual int pcl::SampleConsensusModel< PointT >::countWithinDistance ( const Eigen::VectorXf &  model_coefficients,
const double  threshold 
)
pure virtual
template<typename PointT>
virtual bool pcl::SampleConsensusModel< PointT >::doSamplesVerifyModel ( const std::set< int > &  indices,
const Eigen::VectorXf &  model_coefficients,
const double  threshold 
)
pure virtual
template<typename PointT>
void pcl::SampleConsensusModel< PointT >::drawIndexSample ( std::vector< int > &  sample)
inlineprotected

Fills a sample array with random samples from the indices_ vector.

Parameters
[out]samplethe set of indices of target_ to analyze

Definition at line 455 of file sac_model.h.

Referenced by pcl::SampleConsensusModel< WeightSACPointType >::getSamples().

template<typename PointT>
void pcl::SampleConsensusModel< PointT >::drawIndexSampleRadius ( std::vector< int > &  sample)
inlineprotected

Fills a sample array with one random sample from the indices_ vector and other random samples that are closer than samples_radius_.

Parameters
[out]samplethe set of indices of target_ to analyze

Definition at line 472 of file sac_model.h.

Referenced by pcl::SampleConsensusModel< WeightSACPointType >::getSamples().

template<typename PointT>
const std::string& pcl::SampleConsensusModel< PointT >::getClassName ( ) const
inline

Get a string representation of the name of this class.

Definition at line 353 of file sac_model.h.

Referenced by pcl::SampleConsensusModel< WeightSACPointType >::isModelValid().

template<typename PointT>
virtual void pcl::SampleConsensusModel< PointT >::getDistancesToModel ( const Eigen::VectorXf &  model_coefficients,
std::vector< double > &  distances 
)
pure virtual
template<typename PointT>
boost::shared_ptr<std::vector<int> > pcl::SampleConsensusModel< PointT >::getIndices ( ) const
inline

Get a pointer to the vector of indices used.

Definition at line 345 of file sac_model.h.

template<typename PointT>
PointCloudConstPtr pcl::SampleConsensusModel< PointT >::getInputCloud ( ) const
inline

Get a pointer to the input point cloud dataset.

Definition at line 321 of file sac_model.h.

template<typename PointT>
unsigned int pcl::SampleConsensusModel< PointT >::getModelSize ( ) const
inline

Return the number of coefficients in the model.

Definition at line 367 of file sac_model.h.

template<typename PointT>
virtual SacModel pcl::SampleConsensusModel< PointT >::getModelType ( ) const
pure virtual
template<typename PointT>
void pcl::SampleConsensusModel< PointT >::getRadiusLimits ( double &  min_radius,
double &  max_radius 
)
inline

Get the minimum and maximum allowable radius limits for the model as set by the user.

Parameters
[out]min_radiusthe resultant minimum radius model
[out]max_radiusthe resultant maximum radius model

Definition at line 392 of file sac_model.h.

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

template<typename PointT>
virtual void pcl::SampleConsensusModel< PointT >::getSamples ( int &  iterations,
std::vector< int > &  samples 
)
inlinevirtual

Get a set of random data samples and return them as point indices.

Parameters
[out]iterationsthe internal number of iterations used by SAC methods
[out]samplesthe resultant model samples

Definition at line 178 of file sac_model.h.

template<typename PointT>
unsigned int pcl::SampleConsensusModel< PointT >::getSampleSize ( ) const
inline

Return the size of a sample from which the model is computed.

Definition at line 360 of file sac_model.h.

Referenced by pcl::SampleConsensusModel< WeightSACPointType >::getSamples().

template<typename PointT>
void pcl::SampleConsensusModel< PointT >::getSamplesMaxDist ( double &  radius)
inline

Get maximum distance allowed when drawing random samples.

Parameters
[out]radiusthe maximum distance (L2 norm)

Definition at line 414 of file sac_model.h.

template<typename PointT>
virtual bool pcl::SampleConsensusModel< PointT >::isModelValid ( const Eigen::VectorXf &  model_coefficients)
inlineprotectedvirtual
template<typename PointT>
virtual bool pcl::SampleConsensusModel< PointT >::isSampleGood ( const std::vector< int > &  samples) const
protectedpure virtual
template<typename PointT>
virtual void pcl::SampleConsensusModel< PointT >::optimizeModelCoefficients ( const std::vector< int > &  inliers,
const Eigen::VectorXf &  model_coefficients,
Eigen::VectorXf &  optimized_coefficients 
)
pure virtual

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

Pure virtual.

Note
: these are the coefficients of the model after refinement (e.g., after a least-squares optimization)
Parameters
[in]inliersthe data inliers supporting the model
[in]model_coefficientsthe initial guess for the model coefficients
[out]optimized_coefficientsthe resultant recomputed coefficients after non-linear optimization

Implemented in pcl::SampleConsensusModelCone< PointT, PointNT >, pcl::SampleConsensusModelCone< pcl::PointXYZRGB, PointNT >, pcl::SampleConsensusModelPlane< PointT >, pcl::SampleConsensusModelCylinder< PointT, PointNT >, pcl::SampleConsensusModelCylinder< pcl::PointXYZRGB, PointNT >, pcl::SampleConsensusModelRegistration< PointT >, pcl::SampleConsensusModelCircle3D< PointT >, pcl::SampleConsensusModelSphere< PointT >, pcl::SampleConsensusModelCircle3D< pcl::PointXYZRGB >, pcl::SampleConsensusModelSphere< pcl::PointXYZRGB >, pcl::SampleConsensusModelCircle2D< PointT >, pcl::SampleConsensusModelCircle2D< pcl::PointXYZRGB >, pcl::SampleConsensusModelStick< PointT >, and pcl::SampleConsensusModelLine< PointT >.

template<typename PointT>
virtual void pcl::SampleConsensusModel< PointT >::projectPoints ( const std::vector< int > &  inliers,
const Eigen::VectorXf &  model_coefficients,
PointCloud projected_points,
bool  copy_data_fields = true 
)
pure virtual

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

Pure virtual.

Parameters
[in]inliersthe data inliers that we want to project on the model
[in]model_coefficientsthe coefficients of a model
[out]projected_pointsthe resultant projected points
[in]copy_data_fieldsset to true (default) if we want the projected_points cloud to be an exact copy of the input dataset minus the point projections on the plane model

Implemented in pcl::SampleConsensusModelCone< PointT, PointNT >, pcl::SampleConsensusModelCone< pcl::PointXYZRGB, PointNT >, pcl::SampleConsensusModelPlane< PointT >, pcl::SampleConsensusModelCylinder< PointT, PointNT >, pcl::SampleConsensusModelCylinder< pcl::PointXYZRGB, PointNT >, pcl::SampleConsensusModelRegistration< PointT >, pcl::SampleConsensusModelSphere< PointT >, pcl::SampleConsensusModelSphere< pcl::PointXYZRGB >, pcl::SampleConsensusModelCircle3D< PointT >, pcl::SampleConsensusModelCircle3D< pcl::PointXYZRGB >, pcl::SampleConsensusModelCircle2D< PointT >, pcl::SampleConsensusModelCircle2D< pcl::PointXYZRGB >, pcl::SampleConsensusModelStick< PointT >, and pcl::SampleConsensusModelLine< PointT >.

template<typename PointT>
int pcl::SampleConsensusModel< PointT >::rnd ( )
inlineprotected
template<typename PointT>
virtual void pcl::SampleConsensusModel< PointT >::selectWithinDistance ( const Eigen::VectorXf &  model_coefficients,
const double  threshold,
std::vector< int > &  inliers 
)
pure virtual
template<typename PointT>
void pcl::SampleConsensusModel< PointT >::setIndices ( const boost::shared_ptr< std::vector< int > > &  indices)
inline

Provide a pointer to the vector of indices that represents the input data.

Parameters
[in]indicesa pointer to the vector of indices that represents the input data.

Definition at line 327 of file sac_model.h.

Referenced by pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::selectBase().

template<typename PointT>
void pcl::SampleConsensusModel< PointT >::setIndices ( const std::vector< int > &  indices)
inline

Provide the vector of indices that represents the input data.

Parameters
[out]indicesthe vector of indices that represents the input data.

Definition at line 337 of file sac_model.h.

template<typename PointT>
virtual void pcl::SampleConsensusModel< PointT >::setInputCloud ( const PointCloudConstPtr cloud)
inlinevirtual

Provide a pointer to the input dataset.

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

Reimplemented in pcl::SampleConsensusModelRegistration< PointT >.

Definition at line 304 of file sac_model.h.

Referenced by pcl::SampleConsensusModel< WeightSACPointType >::SampleConsensusModel(), and pcl::SampleConsensusModelRegistration< PointT >::setInputCloud().

template<typename PointT>
void pcl::SampleConsensusModel< PointT >::setRadiusLimits ( const double &  min_radius,
const double &  max_radius 
)
inline

Set the minimum and maximum allowable radius limits for the model (applicable to models that estimate a radius)

Parameters
[in]min_radiusthe minimum radius model
[in]max_radiusthe maximum radius model

Definition at line 379 of file sac_model.h.

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

template<typename PointT>
void pcl::SampleConsensusModel< PointT >::setSamplesMaxDist ( const double &  radius,
SearchPtr  search 
)
inline

Set the maximum distance allowed when drawing random samples.

Parameters
[in]radiusthe maximum distance (L2 norm)
search

Definition at line 403 of file sac_model.h.

Friends And Related Function Documentation

template<typename PointT>
friend class ProgressiveSampleConsensus< PointT >
friend

Definition at line 419 of file sac_model.h.

Member Data Documentation

template<typename PointT>
std::vector<double> pcl::SampleConsensusModel< PointT >::error_sqr_dists_
protected

A vector holding the distances to the computed model.

Used internally.

Definition at line 569 of file sac_model.h.

Referenced by pcl::SampleConsensusModel< WeightSACPointType >::computeVariance().

template<typename PointT>
boost::shared_ptr<std::vector<int> > pcl::SampleConsensusModel< PointT >::indices_
protected
template<typename PointT>
PointCloudConstPtr pcl::SampleConsensusModel< PointT >::input_
protected
template<typename PointT>
const unsigned int pcl::SampleConsensusModel< PointT >::max_sample_checks_ = 1000
staticprotected

The maximum number of samples to try until we get a good one.

Definition at line 543 of file sac_model.h.

Referenced by pcl::SampleConsensusModel< WeightSACPointType >::getSamples().

template<typename PointT>
std::string pcl::SampleConsensusModel< PointT >::model_name_
protected

The model name.

Definition at line 534 of file sac_model.h.

Referenced by pcl::SampleConsensusModel< WeightSACPointType >::getClassName(), pcl::SampleConsensusModelCircle2D< pcl::PointXYZRGB >::SampleConsensusModelCircle2D(), pcl::SampleConsensusModelCircle3D< pcl::PointXYZRGB >::SampleConsensusModelCircle3D(), pcl::SampleConsensusModelCone< pcl::PointXYZRGB, PointNT >::SampleConsensusModelCone(), pcl::SampleConsensusModelCylinder< pcl::PointXYZRGB, PointNT >::SampleConsensusModelCylinder(), pcl::SampleConsensusModelLine< PointT >::SampleConsensusModelLine(), pcl::SampleConsensusModelNormalParallelPlane< PointT, PointNT >::SampleConsensusModelNormalParallelPlane(), pcl::SampleConsensusModelNormalPlane< PointT, PointNT >::SampleConsensusModelNormalPlane(), pcl::SampleConsensusModelNormalSphere< PointT, PointNT >::SampleConsensusModelNormalSphere(), pcl::SampleConsensusModelParallelLine< PointT >::SampleConsensusModelParallelLine(), pcl::SampleConsensusModelParallelPlane< PointT >::SampleConsensusModelParallelPlane(), pcl::SampleConsensusModelPerpendicularPlane< PointT >::SampleConsensusModelPerpendicularPlane(), pcl::SampleConsensusModelPlane< PointT >::SampleConsensusModelPlane(), pcl::SampleConsensusModelRegistration< PointT >::SampleConsensusModelRegistration(), pcl::SampleConsensusModelRegistration2D< PointT >::SampleConsensusModelRegistration2D(), pcl::SampleConsensusModelSphere< pcl::PointXYZRGB >::SampleConsensusModelSphere(), and pcl::SampleConsensusModelStick< PointT >::SampleConsensusModelStick().

template<typename PointT>
unsigned int pcl::SampleConsensusModel< PointT >::model_size_
protected

The number of coefficients in the model.

Every subclass should initialize this appropriately.

Definition at line 575 of file sac_model.h.

Referenced by pcl::SampleConsensusModel< WeightSACPointType >::getModelSize(), pcl::SampleConsensusModel< WeightSACPointType >::isModelValid(), pcl::SampleConsensusModelCircle2D< pcl::PointXYZRGB >::SampleConsensusModelCircle2D(), pcl::SampleConsensusModelCircle3D< pcl::PointXYZRGB >::SampleConsensusModelCircle3D(), pcl::SampleConsensusModelCone< pcl::PointXYZRGB, PointNT >::SampleConsensusModelCone(), pcl::SampleConsensusModelCylinder< pcl::PointXYZRGB, PointNT >::SampleConsensusModelCylinder(), pcl::SampleConsensusModelLine< PointT >::SampleConsensusModelLine(), pcl::SampleConsensusModelNormalParallelPlane< PointT, PointNT >::SampleConsensusModelNormalParallelPlane(), pcl::SampleConsensusModelNormalPlane< PointT, PointNT >::SampleConsensusModelNormalPlane(), pcl::SampleConsensusModelNormalSphere< PointT, PointNT >::SampleConsensusModelNormalSphere(), pcl::SampleConsensusModelParallelLine< PointT >::SampleConsensusModelParallelLine(), pcl::SampleConsensusModelParallelPlane< PointT >::SampleConsensusModelParallelPlane(), pcl::SampleConsensusModelPerpendicularPlane< PointT >::SampleConsensusModelPerpendicularPlane(), pcl::SampleConsensusModelPlane< PointT >::SampleConsensusModelPlane(), pcl::SampleConsensusModelRegistration< PointT >::SampleConsensusModelRegistration(), pcl::SampleConsensusModelRegistration2D< PointT >::SampleConsensusModelRegistration2D(), pcl::SampleConsensusModelSphere< pcl::PointXYZRGB >::SampleConsensusModelSphere(), and pcl::SampleConsensusModelStick< PointT >::SampleConsensusModelStick().

template<typename PointT>
double pcl::SampleConsensusModel< PointT >::radius_max_
protected
template<typename PointT>
double pcl::SampleConsensusModel< PointT >::radius_min_
protected

The minimum and maximum radius limits for the model.

Applicable to all models that estimate a radius.

Definition at line 548 of file sac_model.h.

Referenced by pcl::SampleConsensusModel< WeightSACPointType >::getRadiusLimits(), pcl::SampleConsensusModelSphere< pcl::PointXYZRGB >::isModelValid(), and pcl::SampleConsensusModel< WeightSACPointType >::setRadiusLimits().

template<typename PointT>
boost::mt19937 pcl::SampleConsensusModel< PointT >::rng_alg_
protected

Boost-based random number generator algorithm.

Definition at line 560 of file sac_model.h.

Referenced by pcl::SampleConsensusModel< WeightSACPointType >::SampleConsensusModel().

template<typename PointT>
boost::shared_ptr<boost::uniform_int<> > pcl::SampleConsensusModel< PointT >::rng_dist_
protected

Boost-based random number generator distribution.

Definition at line 563 of file sac_model.h.

Referenced by pcl::SampleConsensusModel< WeightSACPointType >::SampleConsensusModel().

template<typename PointT>
boost::shared_ptr<boost::variate_generator< boost::mt19937&, boost::uniform_int<> > > pcl::SampleConsensusModel< PointT >::rng_gen_
protected
template<typename PointT>
unsigned int pcl::SampleConsensusModel< PointT >::sample_size_
protected

The size of a sample from which the model is computed.

Every subclass should initialize this appropriately.

Definition at line 572 of file sac_model.h.

Referenced by pcl::SampleConsensusModel< WeightSACPointType >::getSampleSize(), pcl::SampleConsensusModelCircle2D< pcl::PointXYZRGB >::SampleConsensusModelCircle2D(), pcl::SampleConsensusModelCircle3D< pcl::PointXYZRGB >::SampleConsensusModelCircle3D(), pcl::SampleConsensusModelCone< pcl::PointXYZRGB, PointNT >::SampleConsensusModelCone(), pcl::SampleConsensusModelCylinder< pcl::PointXYZRGB, PointNT >::SampleConsensusModelCylinder(), pcl::SampleConsensusModelLine< PointT >::SampleConsensusModelLine(), pcl::SampleConsensusModelNormalParallelPlane< PointT, PointNT >::SampleConsensusModelNormalParallelPlane(), pcl::SampleConsensusModelNormalPlane< PointT, PointNT >::SampleConsensusModelNormalPlane(), pcl::SampleConsensusModelNormalSphere< PointT, PointNT >::SampleConsensusModelNormalSphere(), pcl::SampleConsensusModelParallelLine< PointT >::SampleConsensusModelParallelLine(), pcl::SampleConsensusModelParallelPlane< PointT >::SampleConsensusModelParallelPlane(), pcl::SampleConsensusModelPerpendicularPlane< PointT >::SampleConsensusModelPerpendicularPlane(), pcl::SampleConsensusModelPlane< PointT >::SampleConsensusModelPlane(), pcl::SampleConsensusModelRegistration< PointT >::SampleConsensusModelRegistration(), pcl::SampleConsensusModelRegistration2D< PointT >::SampleConsensusModelRegistration2D(), pcl::SampleConsensusModelSphere< pcl::PointXYZRGB >::SampleConsensusModelSphere(), and pcl::SampleConsensusModelStick< PointT >::SampleConsensusModelStick().

template<typename PointT>
double pcl::SampleConsensusModel< PointT >::samples_radius_
protected
template<typename PointT>
SearchPtr pcl::SampleConsensusModel< PointT >::samples_radius_search_
protected

The search object for picking subsequent samples using radius search.

Definition at line 554 of file sac_model.h.

Referenced by pcl::SampleConsensusModel< WeightSACPointType >::drawIndexSampleRadius(), and pcl::SampleConsensusModel< WeightSACPointType >::setSamplesMaxDist().

template<typename PointT>
std::vector<int> pcl::SampleConsensusModel< PointT >::shuffled_indices_
protected

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