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

SampleConsensusModelNormalPlane defines a model for 3D plane segmentation using additional surface normal constraints. More...

#include <pcl/sample_consensus/sac_model_normal_plane.h>

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List of all members.

Public Types

typedef SampleConsensusModel
< PointT >::PointCloud 
PointCloud
typedef SampleConsensusModel
< PointT >::PointCloudPtr 
PointCloudPtr
typedef SampleConsensusModel
< PointT >::PointCloudConstPtr 
PointCloudConstPtr
typedef
SampleConsensusModelFromNormals
< PointT, PointNT >
::PointCloudNPtr 
PointCloudNPtr
typedef
SampleConsensusModelFromNormals
< PointT, PointNT >
::PointCloudNConstPtr 
PointCloudNConstPtr
typedef boost::shared_ptr
< SampleConsensusModelNormalPlane
Ptr
typedef boost::shared_ptr
< const
SampleConsensusModelFromNormals
ConstPtr

Public Member Functions

 SampleConsensusModelNormalPlane (const PointCloudConstPtr &cloud)
 Constructor for base SampleConsensusModelNormalPlane.
 SampleConsensusModelNormalPlane (const PointCloudConstPtr &cloud, const std::vector< int > &indices)
 Constructor for base SampleConsensusModelNormalPlane.
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 getDistancesToModel (const Eigen::VectorXf &model_coefficients, std::vector< double > &distances)
 Compute all distances from the cloud data to a given plane model.
pcl::SacModel getModelType () const
 Return an unique id for this model (SACMODEL_NORMAL_PLANE).
bool computeModelCoefficients (const std::vector< int > &samples, Eigen::VectorXf &model_coefficients)
 Check whether the given index samples can form a valid plane model, compute the model coefficients from these samples and store them internally in model_coefficients_.
void optimizeModelCoefficients (const std::vector< int > &inliers, const Eigen::VectorXf &model_coefficients, Eigen::VectorXf &optimized_coefficients)
 Recompute the plane 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 plane 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 plane model coefficients.
void setNormalDistanceWeight (const double w)
 Set the normal angular distance weight.
double getNormalDistanceWeight ()
 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 ()
 Get a pointer to the normals of the input XYZ point cloud dataset.

Detailed Description

SampleConsensusModelNormalPlane defines a model for 3D plane segmentation using additional surface normal constraints.

Basically this means that checking for inliers will not only involve a "distance to model" criterion, but also an additional "maximum angular deviation" between the plane's normal and the inlier points normals.

The model coefficients are defined as:

To set the influence of the surface normals in the inlier estimation process, set the normal weight (0.0-1.0), e.g.:

 SampleConsensusModelNormalPlane<pcl::PointXYZ, pcl::Normal> sac_model;
 ...
 sac_model.setNormalDistanceWeight (0.1);
 ...
Author:
Radu Bogdan Rusu and Jared Glover

Member Typedef Documentation

Definition at line 379 of file sac_model.h.

Reimplemented from pcl::SampleConsensusModelPlane< PointT >.

Definition at line 86 of file sac_model_normal_plane.h.

Reimplemented from pcl::SampleConsensusModelPlane< PointT >.

Definition at line 88 of file sac_model_normal_plane.h.

Reimplemented from pcl::SampleConsensusModelPlane< PointT >.

Definition at line 87 of file sac_model_normal_plane.h.


Constructor & Destructor Documentation

pcl::SampleConsensusModelNormalPlane::SampleConsensusModelNormalPlane ( const PointCloudConstPtr cloud) [inline]

Constructor for base SampleConsensusModelNormalPlane.

Parameters:
[in]cloudthe input point cloud dataset

Definition at line 98 of file sac_model_normal_plane.h.

pcl::SampleConsensusModelNormalPlane::SampleConsensusModelNormalPlane ( const PointCloudConstPtr cloud,
const std::vector< int > &  indices 
) [inline]

Constructor for base SampleConsensusModelNormalPlane.

Parameters:
[in]cloudthe input point cloud dataset
[in]indicesa vector of point indices to be used from cloud

Definition at line 106 of file sac_model_normal_plane.h.


Member Function Documentation

bool pcl::SampleConsensusModelPlane::computeModelCoefficients ( const std::vector< int > &  samples,
Eigen::VectorXf &  model_coefficients 
) [inherited]

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

The plane coefficients are: a, b, c, d (ax+by+cz+d=0)

Parameters:
[in]samplesthe point indices found as possible good candidates for creating a valid model
[out]model_coefficientsthe resultant model coefficients
int pcl::SampleConsensusModelNormalPlane::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

Reimplemented from pcl::SampleConsensusModelPlane< PointT >.

Definition at line 93 of file sac_model_normal_plane.hpp.

bool pcl::SampleConsensusModelPlane::doSamplesVerifyModel ( const std::set< int > &  indices,
const Eigen::VectorXf &  model_coefficients,
const double  threshold 
) [inherited]

Verify whether a subset of indices verifies the given plane model coefficients.

Parameters:
[in]indicesthe data indices that need to be tested against the plane model
[in]model_coefficientsthe plane model coefficients
[in]thresholda maximum admissible distance threshold for determining the inliers from the outliers
void pcl::SampleConsensusModelNormalPlane::getDistancesToModel ( const Eigen::VectorXf &  model_coefficients,
std::vector< double > &  distances 
)

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

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

Reimplemented from pcl::SampleConsensusModelPlane< PointT >.

Definition at line 133 of file sac_model_normal_plane.hpp.

PointCloudNConstPtr pcl::SampleConsensusModelFromNormals::getInputNormals ( ) [inline, inherited]

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

Definition at line 412 of file sac_model.h.

pcl::SacModel pcl::SampleConsensusModelNormalPlane::getModelType ( ) const [inline]

Return an unique id for this model (SACMODEL_NORMAL_PLANE).

Reimplemented from pcl::SampleConsensusModelPlane< PointT >.

Definition at line 140 of file sac_model_normal_plane.h.

double pcl::SampleConsensusModelFromNormals::getNormalDistanceWeight ( ) [inline, inherited]

Get the normal angular distance weight.

Definition at line 397 of file sac_model.h.

void pcl::SampleConsensusModelPlane::optimizeModelCoefficients ( const std::vector< int > &  inliers,
const Eigen::VectorXf &  model_coefficients,
Eigen::VectorXf &  optimized_coefficients 
) [inherited]

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

Note:
: these are the coefficients of the plane model after refinement (eg. after SVD)
Parameters:
[in]inliersthe data inliers found as supporting the model
[in]model_coefficientsthe initial guess for the model coefficients
[out]optimized_coefficientsthe resultant recomputed coefficients after non-linear optimization
void pcl::SampleConsensusModelPlane::projectPoints ( const std::vector< int > &  inliers,
const Eigen::VectorXf &  model_coefficients,
PointCloud projected_points,
bool  copy_data_fields = true 
) [inherited]

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

Parameters:
[in]inliersthe data inliers that we want to project on the plane model
[in]model_coefficientsthe *normalized* coefficients of a plane model
[out]projected_pointsthe resultant projected points
[in]copy_data_fieldsset to true if we need to copy the other data fields
void pcl::SampleConsensusModelNormalPlane::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.

Parameters:
[in]model_coefficientsthe coefficients of a plane 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

Reimplemented from pcl::SampleConsensusModelPlane< PointT >.

Definition at line 45 of file sac_model_normal_plane.hpp.

void pcl::SampleConsensusModelFromNormals::setInputNormals ( const PointCloudNConstPtr normals) [inline, inherited]

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

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

Definition at line 405 of file sac_model.h.

void pcl::SampleConsensusModelFromNormals::setNormalDistanceWeight ( const double  w) [inline, inherited]

Set the normal angular distance weight.

Parameters:
[in]wthe relative weight (between 0 and 1) to give to the angular distance (0 to pi/2) between point normals and the plane normal. (The Euclidean distance will have weight 1-w.)

Definition at line 390 of file sac_model.h.


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