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

IntensitySpinEstimation estimates the intensity-domain spin image descriptors for a given point cloud dataset containing points and intensity. More...

#include <pcl/features/intensity_spin.h>

Inheritance diagram for pcl::IntensitySpinEstimation:
Inheritance graph
[legend]
Collaboration diagram for pcl::IntensitySpinEstimation:
Collaboration graph
[legend]

List of all members.

Public Types

typedef pcl::PointCloud< PointInT > PointCloudIn
typedef Feature< PointInT,
PointOutT >::PointCloudOut 
PointCloudOut
typedef PCLBase< PointInT > BaseClass
typedef boost::shared_ptr
< Feature< PointInT, PointOutT > > 
Ptr
typedef boost::shared_ptr
< const Feature< PointInT,
PointOutT > > 
ConstPtr
typedef pcl::search::Search
< PointInT > 
KdTree
typedef pcl::search::Search
< PointInT >::Ptr 
KdTreePtr
typedef PointCloudIn::Ptr PointCloudInPtr
typedef PointCloudIn::ConstPtr PointCloudInConstPtr
typedef boost::function< int(size_t,
double, std::vector< int >
&, std::vector< float > &)> 
SearchMethod
typedef boost::function< int(const
PointCloudIn &cloud, size_t
index, double, std::vector
< int > &, std::vector< float > &)> 
SearchMethodSurface

Public Member Functions

 IntensitySpinEstimation ()
 Empty constructor.
void computeIntensitySpinImage (const PointCloudIn &cloud, float radius, float sigma, int k, const std::vector< int > &indices, const std::vector< float > &squared_distances, Eigen::MatrixXf &intensity_spin_image)
 Estimate the intensity-domain spin image descriptor for a given point based on its spatial neighborhood of 3D points and their intensities.
void setNrDistanceBins (size_t nr_distance_bins)
 Set the number of bins to use in the distance dimension of the spin image.
int getNrDistanceBins ()
 Returns the number of bins in the distance dimension of the spin image.
void setNrIntensityBins (size_t nr_intensity_bins)
 Set the number of bins to use in the intensity dimension of the spin image.
int getNrIntensityBins ()
 Returns the number of bins in the intensity dimension of the spin image.
void setSmoothingBandwith (float sigma)
 Set the standard deviation of the Gaussian smoothing kernel to use when constructing the spin images.
float getSmoothingBandwith ()
 Returns the standard deviation of the Gaussian smoothing kernel used to construct the spin images.
void setSearchSurface (const PointCloudInConstPtr &cloud)
 Provide a pointer to a dataset to add additional information to estimate the features for every point in the input dataset.
PointCloudInConstPtr getSearchSurface ()
 Get a pointer to the surface point cloud dataset.
void setSearchMethod (const KdTreePtr &tree)
 Provide a pointer to the search object.
KdTreePtr getSearchMethod ()
 Get a pointer to the search method used.
double getSearchParameter ()
 Get the internal search parameter.
void setKSearch (int k)
 Set the number of k nearest neighbors to use for the feature estimation.
int getKSearch ()
 get the number of k nearest neighbors used for the feature estimation.
void setRadiusSearch (double radius)
 Set the sphere radius that is to be used for determining the nearest neighbors used for the feature estimation.
double getRadiusSearch ()
 Get the sphere radius used for determining the neighbors.
void compute (PointCloudOut &output)
 Base method for feature estimation for all points given in <setInputCloud (), setIndices ()> using the surface in setSearchSurface () and the spatial locator in setSearchMethod ()
int searchForNeighbors (size_t index, double parameter, std::vector< int > &indices, std::vector< float > &distances) const
 Search for k-nearest neighbors using the spatial locator from setSearchmethod, and the given surface from setSearchSurface.
int searchForNeighbors (const PointCloudIn &cloud, size_t index, double parameter, std::vector< int > &indices, std::vector< float > &distances) const
 Search for k-nearest neighbors using the spatial locator from setSearchmethod, and the given surface from setSearchSurface.

Detailed Description

IntensitySpinEstimation estimates the intensity-domain spin image descriptors for a given point cloud dataset containing points and intensity.

For more information about the intensity-domain spin image descriptor, see:

Svetlana Lazebnik, Cordelia Schmid, and Jean Ponce. A sparse texture representation using local affine regions. In IEEE Transactions on Pattern Analysis and Machine Intelligence, volume 27, pages 1265-1278, August 2005.

Author:
Michael Dixon

Member Typedef Documentation

typedef PCLBase<PointInT> pcl::Feature::BaseClass [inherited]

Definition at line 103 of file feature.h.

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

Reimplemented in pcl::FeatureFromNormals.

Definition at line 106 of file feature.h.

typedef pcl::search::Search<PointInT> pcl::Feature::KdTree [inherited]

Definition at line 108 of file feature.h.

typedef pcl::search::Search<PointInT>::Ptr pcl::Feature::KdTreePtr [inherited]

Definition at line 109 of file feature.h.

Reimplemented from pcl::Feature< PointInT, PointOutT >.

Definition at line 68 of file intensity_spin.h.

Definition at line 113 of file feature.h.

Definition at line 112 of file feature.h.

Reimplemented from pcl::Feature< PointInT, PointOutT >.

Definition at line 69 of file intensity_spin.h.

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

Reimplemented in pcl::FeatureFromNormals.

Definition at line 105 of file feature.h.

typedef boost::function<int (size_t, double, std::vector<int> &, std::vector<float> &)> pcl::Feature::SearchMethod [inherited]

Definition at line 117 of file feature.h.

typedef boost::function<int (const PointCloudIn &cloud, size_t index, double, std::vector<int> &, std::vector<float> &)> pcl::Feature::SearchMethodSurface [inherited]

Definition at line 118 of file feature.h.


Constructor & Destructor Documentation

pcl::IntensitySpinEstimation::IntensitySpinEstimation ( ) [inline]

Empty constructor.

Definition at line 72 of file intensity_spin.h.


Member Function Documentation

void pcl::Feature::compute ( PointCloudOut output) [inherited]

Base method for feature estimation for all points given in <setInputCloud (), setIndices ()> using the surface in setSearchSurface () and the spatial locator in setSearchMethod ()

Parameters:
outputthe resultant point cloud model dataset containing the estimated features
void pcl::IntensitySpinEstimation::computeIntensitySpinImage ( const PointCloudIn cloud,
float  radius,
float  sigma,
int  k,
const std::vector< int > &  indices,
const std::vector< float > &  squared_distances,
Eigen::MatrixXf &  intensity_spin_image 
)

Estimate the intensity-domain spin image descriptor for a given point based on its spatial neighborhood of 3D points and their intensities.

Parameters:
cloudthe dataset containing the Cartesian coordinates and intensity values of the points
radiusthe radius of the feature
sigmathe standard deviation of the Gaussian smoothing kernel to use during the soft histogram update
kthe number of neighbors to use from indices and squared_distances
indicesthe indices of the points that comprise the query point's neighborhood
squared_distancesthe squared distances from the query point to each point in the neighborhood
intensity_spin_imagethe resultant intensity-domain spin image descriptor

Definition at line 45 of file intensity_spin.hpp.

int pcl::Feature::getKSearch ( ) [inline, inherited]

get the number of k nearest neighbors used for the feature estimation.

Definition at line 166 of file feature.h.

int pcl::IntensitySpinEstimation::getNrDistanceBins ( ) [inline]

Returns the number of bins in the distance dimension of the spin image.

Definition at line 102 of file intensity_spin.h.

int pcl::IntensitySpinEstimation::getNrIntensityBins ( ) [inline]

Returns the number of bins in the intensity dimension of the spin image.

Definition at line 112 of file intensity_spin.h.

double pcl::Feature::getRadiusSearch ( ) [inline, inherited]

Get the sphere radius used for determining the neighbors.

Definition at line 177 of file feature.h.

KdTreePtr pcl::Feature::getSearchMethod ( ) [inline, inherited]

Get a pointer to the search method used.

Definition at line 152 of file feature.h.

double pcl::Feature::getSearchParameter ( ) [inline, inherited]

Get the internal search parameter.

Definition at line 156 of file feature.h.

PointCloudInConstPtr pcl::Feature::getSearchSurface ( ) [inline, inherited]

Get a pointer to the surface point cloud dataset.

Definition at line 142 of file feature.h.

float pcl::IntensitySpinEstimation::getSmoothingBandwith ( ) [inline]

Returns the standard deviation of the Gaussian smoothing kernel used to construct the spin images.

Definition at line 122 of file intensity_spin.h.

int pcl::Feature::searchForNeighbors ( size_t  index,
double  parameter,
std::vector< int > &  indices,
std::vector< float > &  distances 
) const [inline, inherited]

Search for k-nearest neighbors using the spatial locator from setSearchmethod, and the given surface from setSearchSurface.

Parameters:
indexthe index of the query point
parameterthe search parameter (either k or radius)
indicesthe resultant vector of indices representing the k-nearest neighbors
distancesthe resultant vector of distances representing the distances from the query point to the k-nearest neighbors

Definition at line 196 of file feature.h.

int pcl::Feature::searchForNeighbors ( const PointCloudIn cloud,
size_t  index,
double  parameter,
std::vector< int > &  indices,
std::vector< float > &  distances 
) const [inline, inherited]

Search for k-nearest neighbors using the spatial locator from setSearchmethod, and the given surface from setSearchSurface.

Parameters:
cloudthe query point cloud
indexthe index of the query point in cloud
parameterthe search parameter (either k or radius)
indicesthe resultant vector of indices representing the k-nearest neighbors
distancesthe resultant vector of distances representing the distances from the query point to the k-nearest neighbors

Definition at line 215 of file feature.h.

void pcl::Feature::setKSearch ( int  k) [inline, inherited]

Set the number of k nearest neighbors to use for the feature estimation.

Parameters:
kthe number of k-nearest neighbors

Definition at line 162 of file feature.h.

void pcl::IntensitySpinEstimation::setNrDistanceBins ( size_t  nr_distance_bins) [inline]

Set the number of bins to use in the distance dimension of the spin image.

Parameters:
nr_distance_binsthe number of bins to use in the distance dimension of the spin image

Definition at line 98 of file intensity_spin.h.

void pcl::IntensitySpinEstimation::setNrIntensityBins ( size_t  nr_intensity_bins) [inline]

Set the number of bins to use in the intensity dimension of the spin image.

Parameters:
nr_intensity_binsthe number of bins to use in the intensity dimension of the spin image

Definition at line 108 of file intensity_spin.h.

void pcl::Feature::setRadiusSearch ( double  radius) [inline, inherited]

Set the sphere radius that is to be used for determining the nearest neighbors used for the feature estimation.

Parameters:
radiusthe sphere radius used as the maximum distance to consider a point a neighbor

Definition at line 173 of file feature.h.

void pcl::Feature::setSearchMethod ( const KdTreePtr tree) [inline, inherited]

Provide a pointer to the search object.

Parameters:
treea pointer to the spatial search object.

Definition at line 148 of file feature.h.

void pcl::Feature::setSearchSurface ( const PointCloudInConstPtr cloud) [inline, inherited]

Provide a pointer to a dataset to add additional information to estimate the features for every point in the input dataset.

This is optional, if this is not set, it will only use the data in the input cloud to estimate the features. This is useful when you only need to compute the features for a downsampled cloud.

Parameters:
clouda pointer to a PointCloud message

Definition at line 133 of file feature.h.

void pcl::IntensitySpinEstimation::setSmoothingBandwith ( float  sigma) [inline]

Set the standard deviation of the Gaussian smoothing kernel to use when constructing the spin images.

Parameters:
sigmathe standard deviation of the Gaussian smoothing kernel to use when constructing the spin images

Definition at line 118 of file intensity_spin.h.


The documentation for this class was generated from the following files:
 All Classes Namespaces Files Functions Variables Typedefs Enumerations Enumerator Friends Defines