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

RIFTEstimation estimates the Rotation Invariant Feature Transform descriptors for a given point cloud dataset containing points and intensity. More...

#include <pcl/features/rift.h>

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

List of all members.

Public Types

typedef pcl::PointCloud< PointInT > PointCloudIn
typedef Feature< PointInT,
PointOutT >::PointCloudOut 
PointCloudOut
typedef pcl::PointCloud
< GradientT > 
PointCloudGradient
typedef PointCloudGradient::Ptr PointCloudGradientPtr
typedef
PointCloudGradient::ConstPtr 
PointCloudGradientConstPtr
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

 RIFTEstimation ()
 Empty constructor.
void setInputGradient (const PointCloudGradientConstPtr &gradient)
 Provide a pointer to the input gradient data.
PointCloudGradientConstPtr getInputGradient ()
 Returns a shared pointer to the input gradient data.
void setNrDistanceBins (size_t nr_distance_bins)
 Set the number of bins to use in the distance dimension of the RIFT descriptor.
int getNrDistanceBins ()
 Returns the number of bins in the distance dimension of the RIFT descriptor.
void setNrGradientBins (size_t nr_gradient_bins)
 Set the number of bins to use in the gradient orientation dimension of the RIFT descriptor.
int getNrGradientBins ()
 Returns the number of bins in the gradient orientation dimension of the RIFT descriptor.
void computeRIFT (const PointCloudIn &cloud, const PointCloudGradient &gradient, int p_idx, float radius, const std::vector< int > &indices, const std::vector< float > &squared_distances, Eigen::MatrixXf &rift_descriptor)
 Estimate the Rotation Invariant Feature Transform (RIFT) descriptor for a given point based on its spatial neighborhood of 3D points and the corresponding intensity gradient vector field.
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

RIFTEstimation estimates the Rotation Invariant Feature Transform descriptors for a given point cloud dataset containing points and intensity.

For more information about the RIFT 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.

Definition at line 72 of file rift.h.

Definition at line 74 of file rift.h.

Definition at line 73 of file rift.h.

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

Definition at line 69 of file rift.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 70 of file rift.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::RIFTEstimation::RIFTEstimation ( ) [inline]

Empty constructor.

Definition at line 77 of file rift.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::RIFTEstimation::computeRIFT ( const PointCloudIn cloud,
const PointCloudGradient gradient,
int  p_idx,
float  radius,
const std::vector< int > &  indices,
const std::vector< float > &  squared_distances,
Eigen::MatrixXf &  rift_descriptor 
)

Estimate the Rotation Invariant Feature Transform (RIFT) descriptor for a given point based on its spatial neighborhood of 3D points and the corresponding intensity gradient vector field.

Parameters:
cloudthe dataset containing the Cartesian coordinates of the points
gradientthe dataset containing the intensity gradient at each point in cloud
p_idxthe index of the query point in cloud (i.e. the center of the neighborhood)
radiusthe radius of the RIFT feature
indicesthe indices of the points that comprise p_idx's neighborhood in cloud
squared_distancesthe squared distances from the query point to each point in the neighborhood
rift_descriptorthe resultant RIFT descriptor

Eigen::Map<Eigen::Vector3f> point (& (cloud.points[indices[idx]].x));

Definition at line 45 of file rift.hpp.

PointCloudGradientConstPtr pcl::RIFTEstimation::getInputGradient ( ) [inline]

Returns a shared pointer to the input gradient data.

Definition at line 90 of file rift.h.

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::RIFTEstimation::getNrDistanceBins ( ) [inline]

Returns the number of bins in the distance dimension of the RIFT descriptor.

Definition at line 101 of file rift.h.

int pcl::RIFTEstimation::getNrGradientBins ( ) [inline]

Returns the number of bins in the gradient orientation dimension of the RIFT descriptor.

Definition at line 112 of file rift.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.

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::RIFTEstimation::setInputGradient ( const PointCloudGradientConstPtr gradient) [inline]

Provide a pointer to the input gradient data.

Parameters:
gradienta pointer to the input gradient data

Definition at line 86 of file rift.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::RIFTEstimation::setNrDistanceBins ( size_t  nr_distance_bins) [inline]

Set the number of bins to use in the distance dimension of the RIFT descriptor.

Parameters:
nr_distance_binsthe number of bins to use in the distance dimension of the RIFT descriptor

Definition at line 97 of file rift.h.

void pcl::RIFTEstimation::setNrGradientBins ( size_t  nr_gradient_bins) [inline]

Set the number of bins to use in the gradient orientation dimension of the RIFT descriptor.

Parameters:
nr_gradient_binsthe number of bins to use in the gradient orientation dimension of the RIFT descriptor

Definition at line 108 of file rift.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.


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