cvfh.h

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 * $Id: cvfh.h 4702 2012-02-23 09:39:33Z gedikli $
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#ifndef PCL_FEATURES_CVFH_H_
#define PCL_FEATURES_CVFH_H_

#include <pcl/features/feature.h>
#include <pcl/features/normal_3d.h>
#include <pcl/features/vfh.h>
#include <pcl/search/pcl_search.h>
#include <pcl/common/common.h>

namespace pcl
{
  template<typename PointInT, typename PointNT, typename PointOutT = pcl::VFHSignature308>
  class CVFHEstimation : public FeatureFromNormals<PointInT, PointNT, PointOutT>
  {
    public:
      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>::surface_;
      using FeatureFromNormals<PointInT, PointNT, PointOutT>::normals_;

      typedef typename Feature<PointInT, PointOutT>::PointCloudOut PointCloudOut;
      typedef typename pcl::search::Search<PointNormal>::Ptr KdTreePtr;
      typedef typename pcl::NormalEstimation<PointNormal, PointNormal> NormalEstimator;
      typedef typename pcl::VFHEstimation<PointInT, PointNT, pcl::VFHSignature308> VFHEstimator;

      CVFHEstimation () :
        vpx_ (0), vpy_ (0), vpz_ (0), 
        leaf_size_ (0.005), curv_threshold_ (0.03), 
        cluster_tolerance_ (leaf_size_ * 3), eps_angle_threshold_ (0.125), min_points_ (50)
      {
        search_radius_ = 0;
        k_ = 1;
        feature_name_ = "CVFHEstimation";
        normalize_bins_ = false;
        radius_normals_ = leaf_size_ * 3;
      }
      ;

      void
      filterNormalsWithHighCurvature (const pcl::PointCloud<PointNT> & cloud, std::vector<int> &indices_out,
                                      std::vector<int> &indices_in, float threshold);

      inline void
      setViewPoint (float vpx, float vpy, float vpz)
      {
        vpx_ = vpx;
        vpy_ = vpy;
        vpz_ = vpz;
      }

      inline void
      setRadiusNormals (float radius_normals)
      {
        radius_normals_ = radius_normals;
      }

      inline void
      getViewPoint (float &vpx, float &vpy, float &vpz)
      {
        vpx = vpx_;
        vpy = vpy_;
        vpz = vpz_;
      }

      inline void
      getCentroidClusters (std::vector<Eigen::Vector3f> & centroids)
      {
        for (size_t i = 0; i < centroids_dominant_orientations_.size (); ++i)
          centroids.push_back (centroids_dominant_orientations_[i]);
      }

      inline void
      getCentroidNormalClusters (std::vector<Eigen::Vector3f> & centroids)
      {
        for (size_t i = 0; i < dominant_normals_.size (); ++i)
          centroids.push_back (dominant_normals_[i]);
      }

      inline void
      setClusterTolerance (float d)
      {
        cluster_tolerance_ = d;
      }

      inline void
      setEPSAngleThreshold (float d)
      {
        eps_angle_threshold_ = d;
      }

      inline void
      setCurvatureThreshold (float d)
      {
        curv_threshold_ = d;
      }

      inline void
      setMinPoints (size_t min)
      {
        min_points_ = min;
      }

      inline void
      setNormalizeBins (bool normalize)
      {
        normalize_bins_ = normalize;
      }

    private:
      float vpx_, vpy_, vpz_;

      float leaf_size_;

      bool normalize_bins_;

      float curv_threshold_;

      float cluster_tolerance_;

      float eps_angle_threshold_;

      size_t min_points_;

      float radius_normals_;

      void
      computeFeature (PointCloudOut &output);

      void
      extractEuclideanClustersSmooth (const pcl::PointCloud<pcl::PointNormal> &cloud,
                                      const pcl::PointCloud<pcl::PointNormal> &normals, float tolerance,
                                      const pcl::search::Search<pcl::PointNormal>::Ptr &tree,
                                      std::vector<pcl::PointIndices> &clusters, double eps_angle,
                                      unsigned int min_pts_per_cluster = 1,
                                      unsigned int max_pts_per_cluster = (std::numeric_limits<int>::max) ());

    protected:
      std::vector<Eigen::Vector3f> centroids_dominant_orientations_;
      std::vector<Eigen::Vector3f> dominant_normals_;

    private:
      void 
      computeFeatureEigen (pcl::PointCloud<Eigen::MatrixXf> &output) {}
  };

}

#endif  //#ifndef PCL_FEATURES_VFH_H_