fpfh_omp.h
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#ifndef PCL_FPFH_OMP_H_
#define PCL_FPFH_OMP_H_
#include <pcl/features/feature.h>
#include <pcl/features/fpfh.h>
namespace pcl
{
/** \brief FPFHEstimationOMP estimates the Fast Point Feature Histogram (FPFH) descriptor for a given point cloud
* dataset containing points and normals, in parallel, using the OpenMP standard.
*
* \note If you use this code in any academic work, please cite:
*
* - R.B. Rusu, N. Blodow, M. Beetz.
* Fast Point Feature Histograms (FPFH) for 3D Registration.
* In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA),
* Kobe, Japan, May 12-17 2009.
* - R.B. Rusu, A. Holzbach, N. Blodow, M. Beetz.
* Fast Geometric Point Labeling using Conditional Random Fields.
* In Proceedings of the 22nd IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS),
* St. Louis, MO, USA, October 11-15 2009.
*
* \attention
* The convention for FPFH features is:
* - if a query point's nearest neighbors cannot be estimated, the FPFH feature will be set to NaN
* (not a number)
* - it is impossible to estimate a FPFH descriptor for a point that
* doesn't have finite 3D coordinates. Therefore, any point that contains
* NaN data on x, y, or z, will have its FPFH feature property set to NaN.
*
* \author Radu B. Rusu
* \ingroup features
*/
template <typename PointInT, typename PointNT, typename PointOutT>
class FPFHEstimationOMP : public FPFHEstimation<PointInT, PointNT, PointOutT>
{
public:
typedef boost::shared_ptr<FPFHEstimationOMP<PointInT, PointNT, PointOutT> > Ptr;
typedef boost::shared_ptr<const FPFHEstimationOMP<PointInT, PointNT, PointOutT> > ConstPtr;
using Feature<PointInT, PointOutT>::feature_name_;
using Feature<PointInT, PointOutT>::getClassName;
using Feature<PointInT, PointOutT>::indices_;
using Feature<PointInT, PointOutT>::k_;
using Feature<PointInT, PointOutT>::search_parameter_;
using Feature<PointInT, PointOutT>::input_;
using Feature<PointInT, PointOutT>::surface_;
using FeatureFromNormals<PointInT, PointNT, PointOutT>::normals_;
using FPFHEstimation<PointInT, PointNT, PointOutT>::hist_f1_;
using FPFHEstimation<PointInT, PointNT, PointOutT>::hist_f2_;
using FPFHEstimation<PointInT, PointNT, PointOutT>::hist_f3_;
using FPFHEstimation<PointInT, PointNT, PointOutT>::weightPointSPFHSignature;
typedef typename Feature<PointInT, PointOutT>::PointCloudOut PointCloudOut;
/** \brief Initialize the scheduler and set the number of threads to use.
* \param[in] nr_threads the number of hardware threads to use (0 sets the value back to automatic)
*/
FPFHEstimationOMP (unsigned int nr_threads = 0) : nr_bins_f1_ (11), nr_bins_f2_ (11), nr_bins_f3_ (11), threads_ (nr_threads)
{
feature_name_ = "FPFHEstimationOMP";
}
/** \brief Initialize the scheduler and set the number of threads to use.
* \param[in] nr_threads the number of hardware threads to use (0 sets the value back to automatic)
*/
inline void
setNumberOfThreads (unsigned int nr_threads = 0) { threads_ = nr_threads; }
private:
/** \brief Estimate the Fast Point Feature Histograms (FPFH) descriptors at a set of points given by
* <setInputCloud (), setIndices ()> using the surface in setSearchSurface () and the spatial locator in
* setSearchMethod ()
* \param[out] output the resultant point cloud model dataset that contains the FPFH feature estimates
*/
void
computeFeature (PointCloudOut &output);
public:
/** \brief The number of subdivisions for each angular feature interval. */
int nr_bins_f1_, nr_bins_f2_, nr_bins_f3_;
private:
/** \brief The number of threads the scheduler should use. */
unsigned int threads_;
};
}
#ifdef PCL_NO_PRECOMPILE
#include <pcl/features/impl/fpfh_omp.hpp>
#endif
#endif //#ifndef PCL_FPFH_OMP_H_
pcl::FPFHEstimationOMP::nr_bins_f3_
int nr_bins_f3_
Definition: fpfh_omp.h:120
pcl::Feature::feature_name_
std::string feature_name_
The feature name.
Definition: feature.h:222
pcl
Definition: cloud_iterator.h:46
pcl::FPFHEstimationOMP::nr_bins_f2_
int nr_bins_f2_
Definition: fpfh_omp.h:120
pcl::FPFHEstimationOMP::PointCloudOut
Feature< PointInT, PointOutT >::PointCloudOut PointCloudOut
Definition: fpfh_omp.h:93
pcl::FPFHEstimationOMP::setNumberOfThreads
void setNumberOfThreads(unsigned int nr_threads=0)
Initialize the scheduler and set the number of threads to use.
Definition: fpfh_omp.h:107
pcl::FeatureFromNormals
Definition: feature.h:310
pcl::FPFHEstimation
FPFHEstimation estimates the Fast Point Feature Histogram (FPFH) descriptor for a given point cloud d...
Definition: fpfh.h:80
pcl::PointCloud
PointCloud represents the base class in PCL for storing collections of 3D points. ...
Definition: projection_matrix.h:53
pcl::FPFHEstimationOMP::Ptr
boost::shared_ptr< FPFHEstimationOMP< PointInT, PointNT, PointOutT > > Ptr
Definition: fpfh_omp.h:78
pcl::FPFHEstimationOMP::nr_bins_f1_
int nr_bins_f1_
The number of subdivisions for each angular feature interval.
Definition: fpfh_omp.h:120
pcl::Feature
Feature represents the base feature class.
Definition: feature.h:105
pcl::FPFHEstimationOMP
FPFHEstimationOMP estimates the Fast Point Feature Histogram (FPFH) descriptor for a given point clou...
Definition: fpfh_omp.h:75
pcl::FPFHEstimationOMP::ConstPtr
boost::shared_ptr< const FPFHEstimationOMP< PointInT, PointNT, PointOutT > > ConstPtr
Definition: fpfh_omp.h:79
pcl::FPFHEstimationOMP::FPFHEstimationOMP
FPFHEstimationOMP(unsigned int nr_threads=0)
Initialize the scheduler and set the number of threads to use.
Definition: fpfh_omp.h:98