esf.h

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 * $Id: pfh.hpp 5027 2012-03-12 03:10:45Z rusu $
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#pragma once
 
#include <pcl/features/feature.h>
#include <pcl/point_types.h>       // for pcl::ESFSignature640
#define GRIDSIZE 64
#define GRIDSIZE_H (GRIDSIZE/2)
#include <vector>
 
namespace pcl
{
  /** \brief @b ESFEstimation estimates the ensemble of shape functions descriptors for a given point cloud
    * dataset containing points. Shape functions are D2, D3, A3.  For more information about the ESF descriptor, see:
    * Walter Wohlkinger and Markus Vincze, "Ensemble of Shape Functions for 3D Object Classification", 
    * IEEE International Conference on Robotics and Biomimetics (IEEE-ROBIO), 2011
    * \author Walter Wohlkinger
    * \ingroup features
    */
 
  template <typename PointInT,  typename PointOutT = pcl::ESFSignature640>
  class ESFEstimation: public Feature<PointInT, PointOutT>
  {
    public:
      using Ptr = shared_ptr<ESFEstimation<PointInT, PointOutT> >;
      using ConstPtr = shared_ptr<const ESFEstimation<PointInT, PointOutT> >;
 
      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_radius_;
      using Feature<PointInT, PointOutT>::input_;
      using Feature<PointInT, PointOutT>::surface_;
 
      using PointCloudIn = pcl::PointCloud<PointInT>;
      using PointCloudOut = typename Feature<PointInT, PointOutT>::PointCloudOut;
 
      /** \brief Empty constructor. */
      ESFEstimation () : local_cloud_ ()
      {
        feature_name_ = "ESFEstimation";
        lut_.resize (GRIDSIZE);
        for (int i = 0; i < GRIDSIZE; ++i)
        {
          lut_[i].resize (GRIDSIZE);
          for (int j = 0; j < GRIDSIZE; ++j)
            lut_[i][j].resize (GRIDSIZE);
        }
        //lut_.resize (boost::extents[GRIDSIZE][GRIDSIZE][GRIDSIZE]);
        search_radius_ = 0;
        k_ = 5;
      }
 
      /** \brief Overloaded computed method from pcl::Feature.
        * \param[out] output the resultant point cloud model dataset containing the estimated features
        */
      void
      compute (PointCloudOut &output);
 
    protected:
 
      /** \brief Estimate the Ensebmel of Shape Function (ESF) descriptors at a set of points given by
        * <setInputCloud (),
        * \param output the resultant point cloud model histogram that contains the ESF feature estimates
        */
      void 
      computeFeature (PointCloudOut &output) override;
 
      /** \brief ... */
      int
      lci (const int x1, const int y1, const int z1, 
           const int x2, const int y2, const int z2, 
           float &ratio, int &incnt, int &pointcount);
     
      /** \brief ... */
      void
      computeESF (PointCloudIn &pc, std::vector<float> &hist);
      
      /** \brief ... */
      void
      voxelize9 (PointCloudIn &cluster);
      
      /** \brief ... */
      void
      cleanup9 (PointCloudIn &cluster);
 
      /** \brief ... */
      void
      scale_points_unit_sphere (const pcl::PointCloud<PointInT> &pc, float scalefactor, Eigen::Vector4f& centroid);
 
    private:
 
      /** \brief ... */
      std::vector<std::vector<std::vector<int> > > lut_;
      
      /** \brief ... */
      PointCloudIn local_cloud_;
  };
}
 
#ifdef PCL_NO_PRECOMPILE
#include <pcl/features/impl/esf.hpp>
#endif