Point Cloud Library (PCL)  1.7.0
Classes | Public Types | Public Member Functions | Protected Member Functions
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 >:

List of all members.

Classes

struct  OptimizationFunctor
 Functor for the optimization function.

Public Types

typedef SampleConsensusModel
< PointT >::PointCloud 
PointCloud
typedef SampleConsensusModel
< PointT >::PointCloudPtr 
PointCloudPtr
typedef SampleConsensusModel
< PointT >::PointCloudConstPtr 
PointCloudConstPtr
typedef boost::shared_ptr
< SampleConsensusModelCone
Ptr

Public Member Functions

 SampleConsensusModelCone (const PointCloudConstPtr &cloud, bool random=false)
 Constructor for base SampleConsensusModelCone.
 SampleConsensusModelCone (const PointCloudConstPtr &cloud, const std::vector< int > &indices, bool random=false)
 Constructor for base SampleConsensusModelCone.
 SampleConsensusModelCone (const SampleConsensusModelCone &source)
 Copy constructor.
virtual ~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 minumum to validate a cone model.
bool computeModelCoefficients (const std::vector< int > &samples, Eigen::VectorXf &model_coefficients)
 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)
 Compute all distances from the cloud data to a given cone model.
void selectWithinDistance (const Eigen::VectorXf &model_coefficients, const double threshold, std::vector< int > &inliers)
 Select all the points which respect the given model coefficients as inliers.
virtual int countWithinDistance (const Eigen::VectorXf &model_coefficients, const double threshold)
 Count all the points which respect the given model coefficients as inliers.
void optimizeModelCoefficients (const std::vector< int > &inliers, const Eigen::VectorXf &model_coefficients, Eigen::VectorXf &optimized_coefficients)
 Recompute the cone coefficients using the given inlier set and return them to the user.
void projectPoints (const std::vector< int > &inliers, const Eigen::VectorXf &model_coefficients, PointCloud &projected_points, bool copy_data_fields=true)
 Create a new point cloud with inliers projected onto the cone model.
bool doSamplesVerifyModel (const std::set< int > &indices, const Eigen::VectorXf &model_coefficients, const double threshold)
 Verify whether a subset of indices verifies the given cone model coefficients.
pcl::SacModel getModelType () const
 Return an unique id for this model (SACMODEL_CONE).

Protected Member Functions

double pointToAxisDistance (const Eigen::Vector4f &pt, const Eigen::VectorXf &model_coefficients)
 Get the distance from a point to a line (represented by a point and a direction)
std::string getName () const
 Get a string representation of the name of this class.
bool isModelValid (const Eigen::VectorXf &model_coefficients)
 Check whether a model is valid given the user constraints.
bool isSampleGood (const std::vector< int > &samples) const
 Check if a sample of indices results in a good sample of points indices.

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 65 of file sac_model_cone.h.


Member Typedef Documentation

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

Reimplemented from pcl::SampleConsensusModel< PointT >.

Definition at line 76 of file sac_model_cone.h.

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

Reimplemented from pcl::SampleConsensusModel< PointT >.

Definition at line 78 of file sac_model_cone.h.

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

Reimplemented from pcl::SampleConsensusModel< PointT >.

Definition at line 77 of file sac_model_cone.h.

template<typename PointT, typename PointNT>
typedef boost::shared_ptr<SampleConsensusModelCone> pcl::SampleConsensusModelCone< PointT, PointNT >::Ptr

Reimplemented from pcl::SampleConsensusModel< PointT >.

Definition at line 80 of file sac_model_cone.h.


Constructor & Destructor Documentation

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 86 of file sac_model_cone.h.

template<typename PointT, typename PointNT>
pcl::SampleConsensusModelCone< PointT, PointNT >::SampleConsensusModelCone ( const PointCloudConstPtr cloud,
const std::vector< int > &  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 102 of file sac_model_cone.h.

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 118 of file sac_model_cone.h.

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

Empty destructor.

Definition at line 127 of file sac_model_cone.h.


Member Function Documentation

template<typename PointT , typename PointNT >
bool pcl::SampleConsensusModelCone< PointT, PointNT >::computeModelCoefficients ( const std::vector< int > &  samples,
Eigen::VectorXf &  model_coefficients 
) [virtual]

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 55 of file sac_model_cone.hpp.

template<typename PointT , typename PointNT >
int pcl::SampleConsensusModelCone< PointT, PointNT >::countWithinDistance ( const Eigen::VectorXf &  model_coefficients,
const double  threshold 
) [virtual]

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 255 of file sac_model_cone.hpp.

References pcl::getAngle3D().

template<typename PointT , typename PointNT >
bool pcl::SampleConsensusModelCone< PointT, PointNT >::doSamplesVerifyModel ( const std::set< int > &  indices,
const Eigen::VectorXf &  model_coefficients,
const double  threshold 
) [virtual]

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 438 of file sac_model_cone.hpp.

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 162 of file sac_model_cone.h.

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

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

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 137 of file sac_model_cone.hpp.

References pcl::getAngle3D().

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

Get the angle epsilon (delta) threshold.

Definition at line 152 of file sac_model_cone.h.

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

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 minumum to validate a cone model.

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

Definition at line 181 of file sac_model_cone.h.

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

template<typename PointT, typename PointNT>
pcl::SacModel pcl::SampleConsensusModelCone< PointT, PointNT >::getModelType ( ) const [inline, virtual]

Return an unique id for this model (SACMODEL_CONE).

Implements pcl::SampleConsensusModel< PointT >.

Definition at line 262 of file sac_model_cone.h.

References pcl::SACMODEL_CONE.

template<typename PointT, typename PointNT>
std::string pcl::SampleConsensusModelCone< PointT, PointNT >::getName ( ) const [inline, protected]

Get a string representation of the name of this class.

Definition at line 274 of file sac_model_cone.h.

template<typename PointT , typename PointNT >
bool pcl::SampleConsensusModelCone< PointT, PointNT >::isModelValid ( const Eigen::VectorXf &  model_coefficients) [protected, virtual]

Check whether a model is valid given the user constraints.

Parameters:
[in]model_coefficientsthe set of model coefficients

Implements pcl::SampleConsensusModel< PointT >.

Definition at line 491 of file sac_model_cone.hpp.

References pcl::getAngle3D().

template<typename PointT , typename PointNT >
bool pcl::SampleConsensusModelCone< PointT, PointNT >::isSampleGood ( const std::vector< int > &  samples) const [protected, virtual]

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 48 of file sac_model_cone.hpp.

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 133 of file sac_model_cone.h.

template<typename PointT , typename PointNT >
void pcl::SampleConsensusModelCone< PointT, PointNT >::optimizeModelCoefficients ( const std::vector< int > &  inliers,
const Eigen::VectorXf &  model_coefficients,
Eigen::VectorXf &  optimized_coefficients 
) [virtual]

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 (eg. 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 309 of file sac_model_cone.hpp.

template<typename PointT , typename PointNT >
double pcl::SampleConsensusModelCone< PointT, PointNT >::pointToAxisDistance ( const Eigen::Vector4f &  pt,
const Eigen::VectorXf &  model_coefficients 
) [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 481 of file sac_model_cone.hpp.

References pcl::sqrPointToLineDistance().

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

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 342 of file sac_model_cone.hpp.

References pcl::PointCloud< PointT >::header, pcl::PointCloud< PointT >::height, pcl::PointCloud< PointT >::is_dense, pcl::PointCloud< PointT >::points, and pcl::PointCloud< PointT >::width.

template<typename PointT , typename PointNT >
void pcl::SampleConsensusModelCone< PointT, PointNT >::selectWithinDistance ( const Eigen::VectorXf &  model_coefficients,
const double  threshold,
std::vector< int > &  inliers 
) [virtual]

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 189 of file sac_model_cone.hpp.

References pcl::getAngle3D().

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 158 of file sac_model_cone.h.

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

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 148 of file sac_model_cone.h.

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

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 allwoable opening angle of a cone model
[in]max_anglethe maximum allwoable opening angle of a cone model

Definition at line 170 of file sac_model_cone.h.

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


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