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

PFHEstimation estimates the Point Feature Histogram (PFH) descriptor for a given point cloud dataset containing points and normals. More...

#include <pcl/features/pfh.h>

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List of all members.

Public Types

typedef Feature< PointInT,
PointOutT >::PointCloudOut 
PointCloudOut
typedef Feature< PointInT,
PointOutT >::PointCloudIn 
PointCloudIn
typedef pcl::PointCloud< PointNT > PointCloudN
typedef PointCloudN::Ptr PointCloudNPtr
typedef PointCloudN::ConstPtr PointCloudNConstPtr
typedef boost::shared_ptr
< FeatureFromNormals< PointInT,
PointNT, PointOutT > > 
Ptr
typedef boost::shared_ptr
< const FeatureFromNormals
< PointInT, PointNT, PointOutT > > 
ConstPtr

Public Member Functions

 PFHEstimation ()
 Empty constructor.
bool computePairFeatures (const pcl::PointCloud< PointInT > &cloud, const pcl::PointCloud< PointNT > &normals, int p_idx, int q_idx, float &f1, float &f2, float &f3, float &f4)
 Compute the 4-tuple representation containing the three angles and one distance between two points represented by Cartesian coordinates and normals.
void computePointPFHSignature (const pcl::PointCloud< PointInT > &cloud, const pcl::PointCloud< PointNT > &normals, const std::vector< int > &indices, int nr_split, Eigen::VectorXf &pfh_histogram)
 Estimate the PFH (Point Feature Histograms) individual signatures of the three angular (f1, f2, f3) features for a given point based on its spatial neighborhood of 3D points with normals.
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

PFHEstimation estimates the Point Feature Histogram (PFH) descriptor for a given point cloud dataset containing points and normals.

Note:
If you use this code in any academic work, please cite:
Note:
The code is stateful as we do not expect this class to be multicore parallelized. Please look at FPFHEstimationOMP for examples on parallel implementations of the FPFH (Fast Point Feature Histogram).
Author:
Radu Bogdan Rusu

Member Typedef Documentation

typedef boost::shared_ptr< const FeatureFromNormals<PointInT, PointNT, PointOutT> > pcl::FeatureFromNormals::ConstPtr [inherited]

Definition at line 290 of file feature.h.

typedef Feature<PointInT, PointOutT>::PointCloudIn pcl::PFHEstimation::PointCloudIn

Reimplemented from pcl::FeatureFromNormals< PointInT, PointNT, PointOutT >.

Definition at line 100 of file pfh.h.

Reimplemented in pcl::SpinImageEstimation.

Definition at line 285 of file feature.h.

Reimplemented in pcl::SpinImageEstimation.

Definition at line 287 of file feature.h.

Reimplemented in pcl::SpinImageEstimation.

Definition at line 286 of file feature.h.

Reimplemented from pcl::FeatureFromNormals< PointInT, PointNT, PointOutT >.

Definition at line 99 of file pfh.h.

typedef boost::shared_ptr< FeatureFromNormals<PointInT, PointNT, PointOutT> > pcl::FeatureFromNormals::Ptr [inherited]

Definition at line 289 of file feature.h.


Constructor & Destructor Documentation

pcl::PFHEstimation::PFHEstimation ( ) [inline]

Empty constructor.

Definition at line 103 of file pfh.h.


Member Function Documentation

bool pcl::PFHEstimation::computePairFeatures ( const pcl::PointCloud< PointInT > &  cloud,
const pcl::PointCloud< PointNT > &  normals,
int  p_idx,
int  q_idx,
float &  f1,
float &  f2,
float &  f3,
float &  f4 
)

Compute the 4-tuple representation containing the three angles and one distance between two points represented by Cartesian coordinates and normals.

Note:
For explanations about the features, please see the literature mentioned above (the order of the features might be different).
Parameters:
cloudthe dataset containing the XYZ Cartesian coordinates of the two points
normalsthe dataset containing the surface normals (assuming normalized vectors) at each point in cloud
p_idxthe index of the first point (source)
q_idxthe index of the second point (target)
f1the first angular feature (angle between the projection of nq_idx and u)
f2the second angular feature (angle between nq_idx and v)
f3the third angular feature (angle between np_idx and |p_idx - q_idx|)
f4the distance feature (p_idx - q_idx)

Definition at line 45 of file pfh.hpp.

void pcl::PFHEstimation::computePointPFHSignature ( const pcl::PointCloud< PointInT > &  cloud,
const pcl::PointCloud< PointNT > &  normals,
const std::vector< int > &  indices,
int  nr_split,
Eigen::VectorXf &  pfh_histogram 
)

Estimate the PFH (Point Feature Histograms) individual signatures of the three angular (f1, f2, f3) features for a given point based on its spatial neighborhood of 3D points with normals.

Parameters:
cloudthe dataset containing the XYZ Cartesian coordinates of the two points
normalsthe dataset containing the surface normals at each point in cloud
indicesthe k-neighborhood point indices in the dataset
nr_splitthe number of subdivisions for each angular feature interval
pfh_histogramthe resultant (combinatorial) PFH histogram representing the feature at the query point

Definition at line 57 of file pfh.hpp.

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

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

Definition at line 312 of file feature.h.

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

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

In case of search surface is set to be different from the input cloud, normals should correspond to the search surface, not the input cloud!

Parameters:
normalsthe const boost shared pointer to a PointCloud of normals. By convention, L2 norm of each normal should be 1.

Definition at line 308 of file feature.h.


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