Point Cloud Library (PCL)  1.3.1
Public Types | Public Member Functions
pcl::SACSegmentationFromNormals Class Reference

SACSegmentationFromNormals represents the PCL nodelet segmentation class for Sample Consensus methods and models that require the use of surface normals for estimation. More...

#include <pcl/segmentation/sac_segmentation.h>

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List of all members.

Public Types

typedef SACSegmentation
< PointT >::PointCloud 
PointCloud
typedef PointCloud::Ptr PointCloudPtr
typedef PointCloud::ConstPtr PointCloudConstPtr
typedef pcl::PointCloud< PointNT > PointCloudN
typedef PointCloudN::Ptr PointCloudNPtr
typedef PointCloudN::ConstPtr PointCloudNConstPtr
typedef SampleConsensus
< PointT >::Ptr 
SampleConsensusPtr
typedef SampleConsensusModel
< PointT >::Ptr 
SampleConsensusModelPtr
typedef
SampleConsensusModelFromNormals
< PointT, PointNT >::Ptr 
SampleConsensusModelFromNormalsPtr

Public Member Functions

 SACSegmentationFromNormals ()
 Empty constructor.
void setInputNormals (const PointCloudNConstPtr &normals)
 Provide a pointer to the input dataset that contains the point normals of the XYZ dataset.
PointCloudNConstPtr getInputNormals ()
 Get a pointer to the normals of the input XYZ point cloud dataset.
void setNormalDistanceWeight (double distance_weight)
 Set the relative weight (between 0 and 1) to give to the angular distance (0 to pi/2) between point normals and the plane normal.
double getNormalDistanceWeight ()
 Get the relative weight (between 0 and 1) to give to the angular distance (0 to pi/2) between point normals and the plane normal.
void setModelType (int model)
 The type of model to use (user given parameter).
int getModelType ()
 Get the type of SAC model used.
SampleConsensusPtr getMethod ()
 Get a pointer to the SAC method used.
SampleConsensusModelPtr getModel ()
 Get a pointer to the SAC model used.
void setMethodType (int method)
 The type of sample consensus method to use (user given parameter).
int getMethodType ()
 Get the type of sample consensus method used.
void setDistanceThreshold (double threshold)
 Distance to the model threshold (user given parameter).
double getDistanceThreshold ()
 Get the distance to the model threshold.
void setMaxIterations (int max_iterations)
 Set the maximum number of iterations before giving up.
int getMaxIterations ()
 Get maximum number of iterations before giving up.
void setProbability (double probability)
 Set the probability of choosing at least one sample free from outliers.
double getProbability ()
 Get the probability of choosing at least one sample free from outliers.
void setOptimizeCoefficients (bool optimize)
 Set to true if a coefficient refinement is required.
bool getOptimizeCoefficients ()
 Get the coefficient refinement internal flag.
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)
 Get the minimum and maximum allowable radius limits for the model as set by the user.
void setAxis (const Eigen::Vector3f &ax)
 Set the axis along which we need to search for a model perpendicular to.
Eigen::Vector3f getAxis ()
 Get the axis along which we need to search for a model perpendicular to.
void setEpsAngle (double ea)
 Set the angle epsilon (delta) threshold.
double getEpsAngle ()
 Get the epsilon (delta) model angle threshold in radians.
virtual void segment (PointIndices &inliers, ModelCoefficients &model_coefficients)
 Base method for segmentation of a model in a PointCloud given by <setInputCloud (), setIndices ()>

Detailed Description

SACSegmentationFromNormals represents the PCL nodelet segmentation class for Sample Consensus methods and models that require the use of surface normals for estimation.


Member Typedef Documentation

Reimplemented from pcl::SACSegmentation< PointT >.

Definition at line 274 of file sac_segmentation.h.

Reimplemented from pcl::SACSegmentation< PointT >.

Definition at line 276 of file sac_segmentation.h.

Definition at line 278 of file sac_segmentation.h.

Definition at line 280 of file sac_segmentation.h.

Definition at line 279 of file sac_segmentation.h.

Reimplemented from pcl::SACSegmentation< PointT >.

Definition at line 275 of file sac_segmentation.h.

Definition at line 284 of file sac_segmentation.h.

Reimplemented from pcl::SACSegmentation< PointT >.

Definition at line 283 of file sac_segmentation.h.

Reimplemented from pcl::SACSegmentation< PointT >.

Definition at line 282 of file sac_segmentation.h.


Constructor & Destructor Documentation

pcl::SACSegmentationFromNormals::SACSegmentationFromNormals ( ) [inline]

Empty constructor.

Definition at line 287 of file sac_segmentation.h.


Member Function Documentation

Eigen::Vector3f pcl::SACSegmentation::getAxis ( ) [inline, inherited]

Get the axis along which we need to search for a model perpendicular to.

Definition at line 186 of file sac_segmentation.h.

double pcl::SACSegmentation::getDistanceThreshold ( ) [inline, inherited]

Get the distance to the model threshold.

Definition at line 122 of file sac_segmentation.h.

double pcl::SACSegmentation::getEpsAngle ( ) [inline, inherited]

Get the epsilon (delta) model angle threshold in radians.

Definition at line 196 of file sac_segmentation.h.

PointCloudNConstPtr pcl::SACSegmentationFromNormals::getInputNormals ( ) [inline]

Get a pointer to the normals of the input XYZ point cloud dataset.

Definition at line 298 of file sac_segmentation.h.

int pcl::SACSegmentation::getMaxIterations ( ) [inline, inherited]

Get maximum number of iterations before giving up.

Definition at line 132 of file sac_segmentation.h.

SampleConsensusPtr pcl::SACSegmentation::getMethod ( ) [inline, inherited]

Get a pointer to the SAC method used.

Definition at line 98 of file sac_segmentation.h.

int pcl::SACSegmentation::getMethodType ( ) [inline, inherited]

Get the type of sample consensus method used.

Definition at line 112 of file sac_segmentation.h.

SampleConsensusModelPtr pcl::SACSegmentation::getModel ( ) [inline, inherited]

Get a pointer to the SAC model used.

Definition at line 102 of file sac_segmentation.h.

int pcl::SACSegmentation::getModelType ( ) [inline, inherited]

Get the type of SAC model used.

Definition at line 94 of file sac_segmentation.h.

double pcl::SACSegmentationFromNormals::getNormalDistanceWeight ( ) [inline]

Get the relative weight (between 0 and 1) to give to the angular distance (0 to pi/2) between point normals and the plane normal.

Definition at line 310 of file sac_segmentation.h.

bool pcl::SACSegmentation::getOptimizeCoefficients ( ) [inline, inherited]

Get the coefficient refinement internal flag.

Definition at line 152 of file sac_segmentation.h.

double pcl::SACSegmentation::getProbability ( ) [inline, inherited]

Get the probability of choosing at least one sample free from outliers.

Definition at line 142 of file sac_segmentation.h.

void pcl::SACSegmentation::getRadiusLimits ( double &  min_radius,
double &  max_radius 
) [inline, inherited]

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

Parameters:
min_radiusthe resultant minimum radius model
max_radiusthe resultant maximum radius model

Definition at line 172 of file sac_segmentation.h.

virtual void pcl::SACSegmentation::segment ( PointIndices inliers,
ModelCoefficients model_coefficients 
) [virtual, inherited]

Base method for segmentation of a model in a PointCloud given by <setInputCloud (), setIndices ()>

Parameters:
inliersthe resultant point indices that support the model found (inliers)
model_coefficientsthe resultant model coefficients
void pcl::SACSegmentation::setAxis ( const Eigen::Vector3f &  ax) [inline, inherited]

Set the axis along which we need to search for a model perpendicular to.

Parameters:
axthe axis along which we need to search for a model perpendicular to

Definition at line 182 of file sac_segmentation.h.

void pcl::SACSegmentation::setDistanceThreshold ( double  threshold) [inline, inherited]

Distance to the model threshold (user given parameter).

Parameters:
thresholdthe distance threshold to use

Definition at line 118 of file sac_segmentation.h.

void pcl::SACSegmentation::setEpsAngle ( double  ea) [inline, inherited]

Set the angle epsilon (delta) threshold.

Parameters:
eathe maximum allowed difference between the model normal and the given axis in radians.

Definition at line 192 of file sac_segmentation.h.

void pcl::SACSegmentationFromNormals::setInputNormals ( const PointCloudNConstPtr normals) [inline]

Provide a pointer to the input dataset that contains the point normals of the XYZ dataset.

Parameters:
normalsthe const boost shared pointer to a PointCloud message

Definition at line 294 of file sac_segmentation.h.

void pcl::SACSegmentation::setMaxIterations ( int  max_iterations) [inline, inherited]

Set the maximum number of iterations before giving up.

Parameters:
max_iterationsthe maximum number of iterations the sample consensus method will run

Definition at line 128 of file sac_segmentation.h.

void pcl::SACSegmentation::setMethodType ( int  method) [inline, inherited]

The type of sample consensus method to use (user given parameter).

Parameters:
methodthe method type (check method_types.h)

Definition at line 108 of file sac_segmentation.h.

void pcl::SACSegmentation::setModelType ( int  model) [inline, inherited]

The type of model to use (user given parameter).

Parameters:
modelthe model type (check model_types.h)

Definition at line 90 of file sac_segmentation.h.

void pcl::SACSegmentationFromNormals::setNormalDistanceWeight ( double  distance_weight) [inline]

Set the relative weight (between 0 and 1) to give to the angular distance (0 to pi/2) between point normals and the plane normal.

Parameters:
distance_weightthe distance/angular weight

Definition at line 305 of file sac_segmentation.h.

void pcl::SACSegmentation::setOptimizeCoefficients ( bool  optimize) [inline, inherited]

Set to true if a coefficient refinement is required.

Parameters:
optimizetrue for enabling model coefficient refinement, false otherwise

Definition at line 148 of file sac_segmentation.h.

void pcl::SACSegmentation::setProbability ( double  probability) [inline, inherited]

Set the probability of choosing at least one sample free from outliers.

Parameters:
probabilitythe model fitting probability

Definition at line 138 of file sac_segmentation.h.

void pcl::SACSegmentation::setRadiusLimits ( const double &  min_radius,
const double &  max_radius 
) [inline, inherited]

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

Parameters:
min_radiusthe minimum radius model
max_radiusthe maximum radius model

Definition at line 161 of file sac_segmentation.h.


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