Point Cloud Library (PCL)
1.9.1
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41 #ifndef PCL_FEATURE_H_
42 #define PCL_FEATURE_H_
45 # pragma GCC system_header
48 #include <boost/function.hpp>
49 #include <boost/bind.hpp>
51 #include <pcl/pcl_base.h>
52 #include <pcl/search/search.h>
69 const Eigen::Vector4f &point,
70 Eigen::Vector4f &plane_parameters,
float &curvature);
86 float &nx,
float &ny,
float &nz,
float &curvature);
104 template <
typename Po
intInT,
typename Po
intOutT>
113 typedef boost::shared_ptr< Feature<PointInT, PointOutT> >
Ptr;
114 typedef boost::shared_ptr< const Feature<PointInT, PointOutT> >
ConstPtr;
125 typedef boost::function<int (
size_t,
double, std::vector<int> &, std::vector<float> &)>
SearchMethod;
245 inline const std::string&
271 std::vector<int> &indices, std::vector<float> &distances)
const
289 std::vector<int> &indices, std::vector<float> &distances)
const
302 EIGEN_MAKE_ALIGNED_OPERATOR_NEW
309 template <
typename Po
intInT,
typename Po
intNT,
typename Po
intOutT>
322 typedef boost::shared_ptr< FeatureFromNormals<PointInT, PointNT, PointOutT> >
Ptr;
323 typedef boost::shared_ptr< const FeatureFromNormals<PointInT, PointNT, PointOutT> >
ConstPtr;
361 EIGEN_MAKE_ALIGNED_OPERATOR_NEW
367 template <
typename Po
intInT,
typename Po
intLT,
typename Po
intOutT>
381 typedef boost::shared_ptr< FeatureFromLabels<PointInT, PointLT, PointOutT> >
Ptr;
382 typedef boost::shared_ptr< const FeatureFromLabels<PointInT, PointLT, PointOutT> >
ConstPtr;
412 inline PointCloudLConstPtr
429 EIGEN_MAKE_ALIGNED_OPERATOR_NEW
446 template <
typename Po
intInT,
typename Po
intRFT>
498 #include <pcl/features/impl/feature.hpp>
500 #endif //#ifndef PCL_FEATURE_H_
virtual ~FeatureFromLabels()
Empty destructor.
FeatureFromLabels()
Empty constructor.
This file defines compatibility wrappers for low level I/O functions.
PointCloudIn::Ptr PointCloudInPtr
virtual ~FeatureFromNormals()
Empty destructor.
boost::shared_ptr< PointCloud< PointInT > > Ptr
double search_parameter_
The actual search parameter (from either search_radius_ or k_).
FeatureWithLocalReferenceFrames provides a public interface for descriptor extractor classes which ne...
PointCloudLRFConstPtr frames_
A boost shared pointer to the local reference frames.
pcl::PointCloud< PointRFT > PointCloudLRF
PointCloudConstPtr input_
The input point cloud dataset.
boost::shared_ptr< pcl::search::Search< PointT > > Ptr
boost::function< int(const PointCloudIn &cloud, size_t index, double, std::vector< int > &, std::vector< float > &)> SearchMethodSurface
boost::shared_ptr< const FeatureFromLabels< PointInT, PointLT, PointOutT > > ConstPtr
virtual bool deinitCompute()
This method should get called after ending the actual computation.
void solvePlaneParameters(const Eigen::Matrix3f &covariance_matrix, const Eigen::Vector4f &point, Eigen::Vector4f &plane_parameters, float &curvature)
Solve the eigenvalues and eigenvectors of a given 3x3 covariance matrix, and estimate the least-squar...
SearchMethodSurface search_method_surface_
The search method template for points.
virtual ~Feature()
Empty destructor.
void setInputReferenceFrames(const PointCloudLRFConstPtr &frames)
Provide a pointer to the input dataset that contains the local reference frames of the XYZ dataset.
double getSearchParameter() const
Get the internal search parameter.
boost::shared_ptr< const Feature< PointInT, PointOutT > > ConstPtr
boost::function< int(size_t, double, std::vector< int > &, std::vector< float > &)> SearchMethod
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 ...
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 ...
PointCloudNConstPtr normals_
A pointer to the input dataset that contains the point normals of the XYZ dataset.
virtual bool initCompute()
This method should get called before starting the actual computation.
Feature()
Empty constructor.
PointCloudInConstPtr getSearchSurface() const
Get a pointer to the surface point cloud dataset.
KdTreePtr getSearchMethod() const
Get a pointer to the search method used.
KdTreePtr tree_
A pointer to the spatial search object.
virtual bool initCompute()
This method should get called before starting the actual computation.
pcl::search::Search< PointInT > KdTree
double search_radius_
The nearest neighbors search radius for each point.
boost::shared_ptr< const FeatureFromNormals< PointInT, PointNT, PointOutT > > ConstPtr
PointCloudN::Ptr PointCloudNPtr
virtual ~FeatureWithLocalReferenceFrames()
Empty destructor.
bool fake_surface_
If no surface is given, we use the input PointCloud as the surface.
PointCloudLRFConstPtr getInputReferenceFrames() const
Get a pointer to the local reference frames.
boost::shared_ptr< FeatureFromLabels< PointInT, PointLT, PointOutT > > Ptr
PointCloudNConstPtr getInputNormals() const
Get a pointer to the normals of the input XYZ point cloud dataset.
void compute(PointCloudOut &output)
Base method for feature estimation for all points given in <setInputCloud (), setIndices ()> using th...
void setInputNormals(const PointCloudNConstPtr &normals)
Provide a pointer to the input dataset that contains the point normals of the XYZ dataset.
pcl::search::Search< PointInT >::Ptr KdTreePtr
void setKSearch(int k)
Set the number of k nearest neighbors to use for the feature estimation.
int k_
The number of K nearest neighbors to use for each point.
PointCloudLRF::ConstPtr PointCloudLRFConstPtr
PointCloudInConstPtr surface_
An input point cloud describing the surface that is to be used for nearest neighbors estimation.
double getRadiusSearch() const
Get the sphere radius used for determining the neighbors.
PointCloudLRF::Ptr PointCloudLRFPtr
void setSearchSurface(const PointCloudInConstPtr &cloud)
Provide a pointer to a dataset to add additional information to estimate the features for every point...
boost::shared_ptr< const PointCloud< PointInT > > ConstPtr
PointCloudN::ConstPtr PointCloudNConstPtr
boost::shared_ptr< Feature< PointInT, PointOutT > > Ptr
void setRadiusSearch(double radius)
Set the sphere radius that is to be used for determining the nearest neighbors used for the feature e...
Feature< PointInT, PointRFT >::Ptr LRFEstimationPtr
Check if frames_ has been correctly initialized and compute it if needed.
boost::shared_ptr< FeatureFromNormals< PointInT, PointNT, PointOutT > > Ptr
pcl::PointCloud< PointInT > PointCloudIn
FeatureFromNormals()
Empty constructor.
int getKSearch() const
get the number of k nearest neighbors used for the feature estimation.
pcl::PointCloud< PointOutT > PointCloudOut
const std::string & getClassName() const
Get a string representation of the name of this class.
std::string feature_name_
The feature name.
bool frames_never_defined_
The user has never set the frames.
PointCloudLConstPtr labels_
A pointer to the input dataset that contains the point labels of the XYZ dataset.
PCLBase< PointInT > BaseClass
pcl::PointCloud< PointNT > PointCloudN
PointCloudLConstPtr getInputLabels() const
Get a pointer to the labels of the input XYZ point cloud dataset.
virtual bool initLocalReferenceFrames(const size_t &indices_size, const LRFEstimationPtr &lrf_estimation=LRFEstimationPtr())
PointCloudIn::ConstPtr PointCloudInConstPtr
void setInputLabels(const PointCloudLConstPtr &labels)
Provide a pointer to the input dataset that contains the point labels of the XYZ dataset.
FeatureWithLocalReferenceFrames()
Empty constructor.
virtual bool initCompute()
This method should get called before starting the actual computation.
void setSearchMethod(const KdTreePtr &tree)
Provide a pointer to the search object.
Feature represents the base feature class.