Point Cloud Library (PCL)
1.3.1
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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>
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. |
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.
typedef PCLBase<PointInT> pcl::Feature::BaseClass [inherited] |
typedef boost::shared_ptr< const Feature<PointInT, PointOutT> > pcl::Feature::ConstPtr [inherited] |
Reimplemented in pcl::FeatureFromNormals.
typedef pcl::search::Search<PointInT> pcl::Feature::KdTree [inherited] |
typedef pcl::search::Search<PointInT>::Ptr pcl::Feature::KdTreePtr [inherited] |
typedef pcl::PointCloud<PointInT> pcl::IntensitySpinEstimation::PointCloudIn |
Reimplemented from pcl::Feature< PointInT, PointOutT >.
Definition at line 68 of file intensity_spin.h.
typedef PointCloudIn::ConstPtr pcl::Feature::PointCloudInConstPtr [inherited] |
typedef PointCloudIn::Ptr pcl::Feature::PointCloudInPtr [inherited] |
typedef Feature<PointInT, PointOutT>::PointCloudOut pcl::IntensitySpinEstimation::PointCloudOut |
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.
typedef boost::function<int (size_t, double, std::vector<int> &, std::vector<float> &)> pcl::Feature::SearchMethod [inherited] |
typedef boost::function<int (const PointCloudIn &cloud, size_t index, double, std::vector<int> &, std::vector<float> &)> pcl::Feature::SearchMethodSurface [inherited] |
pcl::IntensitySpinEstimation::IntensitySpinEstimation | ( | ) | [inline] |
Empty constructor.
Definition at line 72 of file intensity_spin.h.
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 ()
output | the 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.
cloud | the dataset containing the Cartesian coordinates and intensity values of the points |
radius | the radius of the feature |
sigma | the standard deviation of the Gaussian smoothing kernel to use during the soft histogram update |
k | the number of neighbors to use from indices and squared_distances |
indices | the indices of the points that comprise the query point's neighborhood |
squared_distances | the squared distances from the query point to each point in the neighborhood |
intensity_spin_image | the resultant intensity-domain spin image descriptor |
Definition at line 45 of file intensity_spin.hpp.
int pcl::Feature::getKSearch | ( | ) | [inline, inherited] |
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] |
KdTreePtr pcl::Feature::getSearchMethod | ( | ) | [inline, inherited] |
double pcl::Feature::getSearchParameter | ( | ) | [inline, inherited] |
PointCloudInConstPtr pcl::Feature::getSearchSurface | ( | ) | [inline, inherited] |
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.
index | the index of the query point |
parameter | the search parameter (either k or radius) |
indices | the resultant vector of indices representing the k-nearest neighbors |
distances | the resultant vector of distances representing the distances from the query point to the k-nearest neighbors |
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.
cloud | the query point cloud |
index | the index of the query point in cloud |
parameter | the search parameter (either k or radius) |
indices | the resultant vector of indices representing the k-nearest neighbors |
distances | the resultant vector of distances representing the distances from the query point to the k-nearest neighbors |
void pcl::Feature::setKSearch | ( | int | k | ) | [inline, inherited] |
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.
nr_distance_bins | the 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.
nr_intensity_bins | the 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] |
void pcl::Feature::setSearchMethod | ( | const KdTreePtr & | tree | ) | [inline, inherited] |
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.
cloud | a pointer to a PointCloud message |
void pcl::IntensitySpinEstimation::setSmoothingBandwith | ( | float | sigma | ) | [inline] |
Set the standard deviation of the Gaussian smoothing kernel to use when constructing the spin images.
sigma | the standard deviation of the Gaussian smoothing kernel to use when constructing the spin images |
Definition at line 118 of file intensity_spin.h.