point_cloud_library / 1.12.1 / classpcl_1_1_sample_consensus_model_sphere.html /

SampleConsensusModelSphere defines a model for 3D sphere segmentation. More...

#include <pcl/sample_consensus/sac_model_sphere.h>

Public Types

using PointCloud = typename SampleConsensusModel< PointT >::PointCloud
using PointCloudPtr = typename SampleConsensusModel< PointT >::PointCloudPtr
using PointCloudConstPtr = typename SampleConsensusModel< PointT >::PointCloudConstPtr
using Ptr = shared_ptr< SampleConsensusModelSphere< PointT > >
using ConstPtr = shared_ptr< const SampleConsensusModelSphere< PointT > >
- 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 Member Functions

SampleConsensusModelSphere (const PointCloudConstPtr &cloud, bool random=false)
Constructor for base SampleConsensusModelSphere. More...
SampleConsensusModelSphere (const PointCloudConstPtr &cloud, const Indices &indices, bool random=false)
Constructor for base SampleConsensusModelSphere. More...
~SampleConsensusModelSphere ()
Empty destructor. More...
SampleConsensusModelSphere (const SampleConsensusModelSphere &source)
Copy constructor. More...
SampleConsensusModelSphere & operator= (const SampleConsensusModelSphere &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 sphere model, compute the model coefficients from these samples and store them internally 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 sphere 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 sphere 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 sphere 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 sphere model coefficients. More...
pcl::SacModel getModelType () const override
Return a unique id for this model (SACMODEL_SPHERE). 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 ()
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...

Protected Member Functions

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...
std::size_t countWithinDistanceStandard (const Eigen::VectorXf &model_coefficients, const double threshold, std::size_t i=0) const
This implementation uses no SIMD instructions. 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...
- 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>
class pcl::SampleConsensusModelSphere< PointT >

SampleConsensusModelSphere defines a model for 3D sphere segmentation.

The model coefficients are defined as:

  • center.x : the X coordinate of the sphere's center
  • center.y : the Y coordinate of the sphere's center
  • center.z : the Z coordinate of the sphere's center
  • radius : the sphere's radius
Author
Radu B. Rusu

Definition at line 66 of file sac_model_sphere.h.

Member Typedef Documentation

ConstPtr

template<typename PointT >
using pcl::SampleConsensusModelSphere< PointT >::ConstPtr = shared_ptr<const SampleConsensusModelSphere<PointT> >

Definition at line 81 of file sac_model_sphere.h.

PointCloud

template<typename PointT >
using pcl::SampleConsensusModelSphere< PointT >::PointCloud = typename SampleConsensusModel<PointT>::PointCloud

Definition at line 76 of file sac_model_sphere.h.

PointCloudConstPtr

Definition at line 78 of file sac_model_sphere.h.

PointCloudPtr

Definition at line 77 of file sac_model_sphere.h.

Ptr

template<typename PointT >
using pcl::SampleConsensusModelSphere< PointT >::Ptr = shared_ptr<SampleConsensusModelSphere<PointT> >

Definition at line 80 of file sac_model_sphere.h.

Constructor & Destructor Documentation

SampleConsensusModelSphere() [1/3]

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

Constructor for base SampleConsensusModelSphere.

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

Definition at line 87 of file sac_model_sphere.h.

SampleConsensusModelSphere() [2/3]

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

Constructor for base SampleConsensusModelSphere.

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

Definition at line 101 of file sac_model_sphere.h.

~SampleConsensusModelSphere()

template<typename PointT >
pcl::SampleConsensusModelSphere< PointT >::~SampleConsensusModelSphere ( )
inline

Empty destructor.

Definition at line 112 of file sac_model_sphere.h.

SampleConsensusModelSphere() [3/3]

template<typename PointT >
pcl::SampleConsensusModelSphere< PointT >::SampleConsensusModelSphere ( const SampleConsensusModelSphere< PointT > & source )
inline

Copy constructor.

Parameters
[in] source the model to copy into this

Definition at line 117 of file sac_model_sphere.h.

Member Function Documentation

computeModelCoefficients()

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

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

The sphere coefficients are: x, y, z, R.

Parameters
[in] samples the point indices found as possible good candidates for creating a valid model
[out] model_coefficients the resultant model coefficients

Implements pcl::SampleConsensusModel< PointT >.

Definition at line 61 of file sac_model_sphere.hpp.

countWithinDistance()

template<typename PointT >
std::size_t pcl::SampleConsensusModelSphere< PointT >::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_coefficients the coefficients of a model that we need to compute distances to
[in] threshold maximum admissible distance threshold for determining the inliers from the outliers
Returns
the resultant number of inliers

Implements pcl::SampleConsensusModel< PointT >.

Definition at line 218 of file sac_model_sphere.hpp.

countWithinDistanceStandard()

template<typename PointT >
std::size_t pcl::SampleConsensusModelSphere< PointT >::countWithinDistanceStandard ( const Eigen::VectorXf & model_coefficients,
const double threshold,
std::size_t i = 0
) const
protected

This implementation uses no SIMD instructions.

It is not intended for normal use. See countWithinDistance which automatically uses the fastest implementation.

Definition at line 236 of file sac_model_sphere.hpp.

doSamplesVerifyModel()

template<typename PointT >
bool pcl::SampleConsensusModelSphere< PointT >::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 sphere model coefficients.

Parameters
[in] indices the data indices that need to be tested against the sphere model
[in] model_coefficients the sphere model coefficients
[in] threshold a maximum admissible distance threshold for determining the inliers from the outliers

Implements pcl::SampleConsensusModel< PointT >.

Definition at line 451 of file sac_model_sphere.hpp.

getDistancesToModel()

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

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

Parameters
[in] model_coefficients the coefficients of a sphere model that we need to compute distances to
[out] distances the resultant estimated distances

Implements pcl::SampleConsensusModel< PointT >.

Definition at line 159 of file sac_model_sphere.hpp.

getModelType()

template<typename PointT >
pcl::SacModel pcl::SampleConsensusModelSphere< PointT >::getModelType ( ) const
inlineoverridevirtual

Return a unique id for this model (SACMODEL_SPHERE).

Implements pcl::SampleConsensusModel< PointT >.

Definition at line 207 of file sac_model_sphere.h.

isModelValid()

template<typename PointT >
bool pcl::SampleConsensusModelSphere< PointT >::isModelValid ( const Eigen::VectorXf & model_coefficients ) const
inlineoverrideprotectedvirtual

Check whether a model is valid given the user constraints.

Parameters
[in] model_coefficients the set of model coefficients

Reimplemented from pcl::SampleConsensusModel< PointT >.

Definition at line 217 of file sac_model_sphere.h.

isSampleGood()

template<typename PointT >
bool pcl::SampleConsensusModelSphere< PointT >::isSampleGood ( const Indices & samples ) const
overrideprotectedvirtual

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

Parameters
[in] samples the resultant index samples

Implements pcl::SampleConsensusModel< PointT >.

Definition at line 49 of file sac_model_sphere.hpp.

operator=()

template<typename PointT >
SampleConsensusModelSphere& pcl::SampleConsensusModelSphere< PointT >::operator= ( const SampleConsensusModelSphere< PointT > & source )
inline

Copy constructor.

Parameters
[in] source the model to copy into this

Definition at line 128 of file sac_model_sphere.h.

optimizeModelCoefficients()

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

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

Note
: these are the coefficients of the sphere model after refinement (e.g. after SVD)
Parameters
[in] inliers the data inliers found as supporting the model
[in] model_coefficients the initial guess for the optimization
[out] optimized_coefficients the resultant recomputed coefficients after non-linear optimization

Implements pcl::SampleConsensusModel< PointT >.

Definition at line 337 of file sac_model_sphere.hpp.

projectPoints()

template<typename PointT >
void pcl::SampleConsensusModelSphere< PointT >::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 sphere model.

Parameters
[in] inliers the data inliers that we want to project on the sphere model
[in] model_coefficients the coefficients of a sphere model
[out] projected_points the resultant projected points
[in] copy_data_fields set to true if we need to copy the other data fields
Todo:
implement this.

Implements pcl::SampleConsensusModel< PointT >.

Definition at line 368 of file sac_model_sphere.hpp.

selectWithinDistance()

template<typename PointT >
void pcl::SampleConsensusModelSphere< PointT >::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_coefficients the coefficients of a sphere model that we need to compute distances to
[in] threshold a maximum admissible distance threshold for determining the inliers from the outliers
[out] inliers the resultant model inliers

Implements pcl::SampleConsensusModel< PointT >.

Definition at line 182 of file sac_model_sphere.hpp.


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_sample_consensus_model_sphere.html