Point Cloud Library (PCL)
1.3.1
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UniformSampling assembles a local 3D grid over a given PointCloud, and downsamples + filters the data. More...
#include <pcl/keypoints/uniform_sampling.h>
Classes | |
struct | Leaf |
Simple structure to hold an nD centroid and the number of points in a leaf. More... | |
Public Types | |
typedef PCLBase< PointInT > | BaseClass |
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(int, double, std::vector< int > &, std::vector< float > &)> | SearchMethod |
typedef boost::function< int(const PointCloudIn &cloud, int index, double, std::vector< int > &, std::vector< float > &)> | SearchMethodSurface |
Public Member Functions | |
UniformSampling () | |
Empty constructor. | |
virtual | ~UniformSampling () |
Destructor. | |
virtual void | setRadiusSearch (double radius) |
Set the 3D grid leaf size. | |
void | setSearchSurface (const PointCloudInConstPtr &cloud) |
Provide a pointer to the input dataset that we need to estimate features at every point for. | |
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. | |
double | getRadiusSearch () |
Get the sphere radius used for determining the neighbors. | |
void | compute (PointCloudOut &output) |
Base method for key point detection for all points given in <setInputCloud (), setIndices ()> using the surface in setSearchSurface () and the spatial locator in setSearchMethod () | |
int | searchForNeighbors (int index, double parameter, std::vector< int > &indices, std::vector< float > &distances) |
Search for k-nearest neighbors using the spatial locator from setSearchmethod, and the given surface from setSearchSurface. |
UniformSampling assembles a local 3D grid over a given PointCloud, and downsamples + filters the data.
The UniformSampling class creates a *3D voxel grid* (think about a voxel grid as a set of tiny 3D boxes in space) over the input point cloud data. Then, in each *voxel* (i.e., 3D box), all the points present will be approximated (i.e., *downsampled*) with their centroid. This approach is a bit slower than approximating them with the center of the voxel, but it represents the underlying surface more accurately.
typedef PCLBase<PointInT> pcl::Keypoint::BaseClass [inherited] |
Definition at line 60 of file keypoint.h.
typedef pcl::search::Search<PointInT> pcl::Keypoint::KdTree [inherited] |
Definition at line 61 of file keypoint.h.
typedef pcl::search::Search<PointInT>::Ptr pcl::Keypoint::KdTreePtr [inherited] |
Definition at line 62 of file keypoint.h.
typedef PointCloudIn::ConstPtr pcl::Keypoint::PointCloudInConstPtr [inherited] |
Definition at line 65 of file keypoint.h.
typedef PointCloudIn::Ptr pcl::Keypoint::PointCloudInPtr [inherited] |
Definition at line 64 of file keypoint.h.
typedef boost::function<int (int, double, std::vector<int> &, std::vector<float> &)> pcl::Keypoint::SearchMethod [inherited] |
Definition at line 67 of file keypoint.h.
typedef boost::function<int (const PointCloudIn &cloud, int index, double, std::vector<int> &, std::vector<float> &)> pcl::Keypoint::SearchMethodSurface [inherited] |
Definition at line 68 of file keypoint.h.
pcl::UniformSampling::UniformSampling | ( | ) | [inline] |
Empty constructor.
Definition at line 74 of file uniform_sampling.h.
virtual pcl::UniformSampling::~UniformSampling | ( | ) | [inline, virtual] |
Destructor.
Definition at line 82 of file uniform_sampling.h.
void pcl::Keypoint::compute | ( | PointCloudOut & | output | ) | [inline, inherited] |
Base method for key point detection 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 |
int pcl::Keypoint::getKSearch | ( | ) | [inline, inherited] |
get the number of k nearest neighbors used for the feature estimation.
Definition at line 106 of file keypoint.h.
double pcl::Keypoint::getRadiusSearch | ( | ) | [inline, inherited] |
Get the sphere radius used for determining the neighbors.
Definition at line 117 of file keypoint.h.
KdTreePtr pcl::Keypoint::getSearchMethod | ( | ) | [inline, inherited] |
Get a pointer to the search method used.
Definition at line 92 of file keypoint.h.
double pcl::Keypoint::getSearchParameter | ( | ) | [inline, inherited] |
Get the internal search parameter.
Definition at line 96 of file keypoint.h.
PointCloudInConstPtr pcl::Keypoint::getSearchSurface | ( | ) | [inline, inherited] |
Get a pointer to the surface point cloud dataset.
Definition at line 82 of file keypoint.h.
int pcl::Keypoint::searchForNeighbors | ( | int | index, |
double | parameter, | ||
std::vector< int > & | indices, | ||
std::vector< float > & | distances | ||
) | [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 |
Definition at line 135 of file keypoint.h.
void pcl::Keypoint::setKSearch | ( | int | k | ) | [inline, inherited] |
Set the number of k nearest neighbors to use for the feature estimation.
k | the number of k-nearest neighbors |
Definition at line 102 of file keypoint.h.
virtual void pcl::UniformSampling::setRadiusSearch | ( | double | radius | ) | [inline, virtual] |
Set the 3D grid leaf size.
radius | the 3D grid leaf size |
Reimplemented from pcl::Keypoint< PointInT, int >.
Definition at line 91 of file uniform_sampling.h.
void pcl::Keypoint::setSearchMethod | ( | const KdTreePtr & | tree | ) | [inline, inherited] |
Provide a pointer to the search object.
tree | a pointer to the spatial search object. |
Definition at line 88 of file keypoint.h.
void pcl::Keypoint::setSearchSurface | ( | const PointCloudInConstPtr & | cloud | ) | [inline, inherited] |
Provide a pointer to the input dataset that we need to estimate features at every point for.
cloud | the const boost shared pointer to a PointCloud message |
Definition at line 78 of file keypoint.h.