shot.h

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#pragma once
 
#include <pcl/point_types.h>
#include <pcl/features/feature.h>
 
#include <array>  // for sRGB_LUT, sXYZ_LUT
 
namespace pcl
{
  /** \brief SHOTEstimation estimates the Signature of Histograms of OrienTations (SHOT) descriptor for
    * a given point cloud dataset containing points and normals.
    *
    * The suggested PointOutT is pcl::SHOT352.
    *
    * \note If you use this code in any academic work, please cite:
    *
    *   - F. Tombari, S. Salti, L. Di Stefano
    *     Unique Signatures of Histograms for Local Surface Description.
    *     In Proceedings of the 11th European Conference on Computer Vision (ECCV),
    *     Heraklion, Greece, September 5-11 2010.
    *   - F. Tombari, S. Salti, L. Di Stefano
    *     A Combined Texture-Shape Descriptor For Enhanced 3D Feature Matching.
    *     In Proceedings of the 18th International Conference on Image Processing (ICIP),
    *     Brussels, Belgium, September 11-14 2011.
    *
    * \author Samuele Salti, Federico Tombari
    * \ingroup features
    */
  template <typename PointInT, typename PointNT, typename PointOutT, typename PointRFT = pcl::ReferenceFrame>
  class SHOTEstimationBase : public FeatureFromNormals<PointInT, PointNT, PointOutT>,
                             public FeatureWithLocalReferenceFrames<PointInT, PointRFT>
  {
    public:
      using Ptr = shared_ptr<SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT> >;
      using ConstPtr = shared_ptr<const SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT> >;
      using Feature<PointInT, PointOutT>::feature_name_;
      using Feature<PointInT, PointOutT>::getClassName;
      using Feature<PointInT, PointOutT>::input_;
      using Feature<PointInT, PointOutT>::indices_;
      using Feature<PointInT, PointOutT>::k_;
      using Feature<PointInT, PointOutT>::search_parameter_;
      using Feature<PointInT, PointOutT>::search_radius_;
      using Feature<PointInT, PointOutT>::surface_;
      using Feature<PointInT, PointOutT>::fake_surface_;
      using FeatureFromNormals<PointInT, PointNT, PointOutT>::normals_;
      using FeatureWithLocalReferenceFrames<PointInT, PointRFT>::frames_;
 
      using PointCloudIn = typename Feature<PointInT, PointOutT>::PointCloudIn;
 
    protected:
      /** \brief Empty constructor.
        * \param[in] nr_shape_bins the number of bins in the shape histogram
        */
      SHOTEstimationBase (int nr_shape_bins = 10) :
        nr_shape_bins_ (nr_shape_bins)
      {
        feature_name_ = "SHOTEstimation";
      }
 
    public:
 
      /** \brief Empty destructor */
      ~SHOTEstimationBase () override = default;
 
       /** \brief Estimate the SHOT descriptor for a given point based on its spatial neighborhood of 3D points with normals
         * \param[in] index the index of the point in indices_
         * \param[in] indices the k-neighborhood point indices in surface_
         * \param[in] sqr_dists the k-neighborhood point distances in surface_
         * \param[out] shot the resultant SHOT descriptor representing the feature at the query point
         */
      virtual void
      computePointSHOT (const int index,
                        const pcl::Indices &indices,
                        const std::vector<float> &sqr_dists,
                        Eigen::VectorXf &shot) = 0;
 
        /** \brief Set the radius used for local reference frame estimation if the frames are not set by the user */
      virtual void
      setLRFRadius (float radius) { lrf_radius_ = radius; }
 
        /** \brief Get the radius used for local reference frame estimation */
      virtual float
      getLRFRadius () const { return lrf_radius_; }
 
    protected:
 
      /** \brief This method should get called before starting the actual computation. */
      bool
      initCompute () override;
 
      /** \brief Quadrilinear interpolation used when color and shape descriptions are NOT activated simultaneously
        *
        * \param[in] indices the neighborhood point indices
        * \param[in] sqr_dists the neighborhood point distances
        * \param[in] index the index of the point in indices_
        * \param[out] binDistance the resultant distance shape histogram
        * \param[in] nr_bins the number of bins in the shape histogram
        * \param[out] shot the resultant SHOT histogram
        */
      void
      interpolateSingleChannel (const pcl::Indices &indices,
                                const std::vector<float> &sqr_dists,
                                const int index,
                                std::vector<double> &binDistance,
                                const int nr_bins,
                                Eigen::VectorXf &shot);
 
      /** \brief Normalize the SHOT histogram.
        * \param[in,out] shot the SHOT histogram
        * \param[in] desc_length the length of the histogram
        */
      void
      normalizeHistogram (Eigen::VectorXf &shot, int desc_length);
 
 
      /** \brief Create a binned distance shape histogram
        * \param[in] index the index of the point in indices_
        * \param[in] indices the k-neighborhood point indices in surface_
        * \param[out] bin_distance_shape the resultant histogram
        */
      void
      createBinDistanceShape (int index, const pcl::Indices &indices,
                              std::vector<double> &bin_distance_shape);
 
      /** \brief The number of bins in each shape histogram. */
      int nr_shape_bins_;
 
      /** \brief The radius used for the LRF computation */
      float lrf_radius_{0.0f};
 
      /** \brief The squared search radius. */
      double sqradius_{0.0};
 
      /** \brief 3/4 of the search radius. */
      double radius3_4_{0.0};
 
      /** \brief 1/4 of the search radius. */
      double radius1_4_{0.0};
 
      /** \brief 1/2 of the search radius. */
      double radius1_2_{0.0};
 
      /** \brief Number of azimuthal sectors. */
      const int nr_grid_sector_{32};
 
      /** \brief ... */
      const int maxAngularSectors_{32};
 
      /** \brief One SHOT length. */
      int descLength_{0};
  };
 
  /** \brief SHOTEstimation estimates the Signature of Histograms of OrienTations (SHOT) descriptor for
    * a given point cloud dataset containing points and normals.
    *
    * The suggested PointOutT is pcl::SHOT352
    *
    * \note If you use this code in any academic work, please cite:
    *
    *   - F. Tombari, S. Salti, L. Di Stefano
    *     Unique Signatures of Histograms for Local Surface Description.
    *     In Proceedings of the 11th European Conference on Computer Vision (ECCV),
    *     Heraklion, Greece, September 5-11 2010.
    *   - F. Tombari, S. Salti, L. Di Stefano
    *     A Combined Texture-Shape Descriptor For Enhanced 3D Feature Matching.
    *     In Proceedings of the 18th International Conference on Image Processing (ICIP),
    *     Brussels, Belgium, September 11-14 2011.
    *
    * \author Samuele Salti, Federico Tombari
    * \ingroup features
    */
  template <typename PointInT, typename PointNT, typename PointOutT = pcl::SHOT352, typename PointRFT = pcl::ReferenceFrame>
  class SHOTEstimation : public SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>
  {
    public:
      using Ptr = shared_ptr<SHOTEstimation<PointInT, PointNT, PointOutT, PointRFT> >;
      using ConstPtr = shared_ptr<const SHOTEstimation<PointInT, PointNT, PointOutT, PointRFT> >;
      using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::feature_name_;
      using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::getClassName;
      using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::indices_;
      using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::k_;
      using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::search_parameter_;
      using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::search_radius_;
      using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::surface_;
      using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::input_;
      using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::normals_;
      using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::descLength_;
      using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::nr_grid_sector_;
      using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::nr_shape_bins_;
      using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::sqradius_;
      using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::radius3_4_;
      using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::radius1_4_;
      using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::radius1_2_;
      using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::maxAngularSectors_;
      using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::interpolateSingleChannel;
      using FeatureWithLocalReferenceFrames<PointInT, PointRFT>::frames_;
 
      using PointCloudIn = typename Feature<PointInT, PointOutT>::PointCloudIn;
 
      /** \brief Empty constructor. */
      SHOTEstimation () : SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT> (10)
      {
        feature_name_ = "SHOTEstimation";
      };
      
      /** \brief Empty destructor */
      ~SHOTEstimation () override = default;
 
      /** \brief Estimate the SHOT descriptor for a given point based on its spatial neighborhood of 3D points with normals
        * \param[in] index the index of the point in indices_
        * \param[in] indices the k-neighborhood point indices in surface_
        * \param[in] sqr_dists the k-neighborhood point distances in surface_
        * \param[out] shot the resultant SHOT descriptor representing the feature at the query point
        */
      void
      computePointSHOT (const int index,
                        const pcl::Indices &indices,
                        const std::vector<float> &sqr_dists,
                        Eigen::VectorXf &shot) override;
    protected:
      /** \brief Estimate the Signatures of Histograms of OrienTations (SHOT) descriptors at a set of points given by
        * <setInputCloud (), setIndices ()> using the surface in setSearchSurface () and the spatial locator in
        * setSearchMethod ()
        * \param output the resultant point cloud model dataset that contains the SHOT feature estimates
        */
      void
      computeFeature (pcl::PointCloud<PointOutT> &output) override;
  };
 
  /** \brief SHOTColorEstimation estimates the Signature of Histograms of OrienTations (SHOT) descriptor for a given point cloud dataset
    * containing points, normals and colors.
    *
    * The suggested PointOutT is pcl::SHOT1344
    *
    * \note If you use this code in any academic work, please cite:
    *
    *   - F. Tombari, S. Salti, L. Di Stefano
    *     Unique Signatures of Histograms for Local Surface Description.
    *     In Proceedings of the 11th European Conference on Computer Vision (ECCV),
    *     Heraklion, Greece, September 5-11 2010.
    *   - F. Tombari, S. Salti, L. Di Stefano
    *     A Combined Texture-Shape Descriptor For Enhanced 3D Feature Matching.
    *     In Proceedings of the 18th International Conference on Image Processing (ICIP),
    *     Brussels, Belgium, September 11-14 2011.
    *
    * \author Samuele Salti, Federico Tombari
    * \ingroup features
    */
  template <typename PointInT, typename PointNT, typename PointOutT = pcl::SHOT1344, typename PointRFT = pcl::ReferenceFrame>
  class SHOTColorEstimation : public SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>
  {
    public:
      using Ptr = shared_ptr<SHOTColorEstimation<PointInT, PointNT, PointOutT, PointRFT> >;
      using ConstPtr = shared_ptr<const SHOTColorEstimation<PointInT, PointNT, PointOutT, PointRFT> >;
      using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::feature_name_;
      using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::getClassName;
      using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::indices_;
      using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::k_;
      using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::search_parameter_;
      using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::search_radius_;
      using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::surface_;
      using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::input_;
      using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::normals_;
      using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::descLength_;
      using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::nr_grid_sector_;
      using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::nr_shape_bins_;
      using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::sqradius_;
      using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::radius3_4_;
      using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::radius1_4_;
      using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::radius1_2_;
      using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::maxAngularSectors_;
      using SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::interpolateSingleChannel;
      using FeatureWithLocalReferenceFrames<PointInT, PointRFT>::frames_;
 
      using PointCloudIn = typename Feature<PointInT, PointOutT>::PointCloudIn;
 
      /** \brief Empty constructor.
        * \param[in] describe_shape
        * \param[in] describe_color
        */
      SHOTColorEstimation (bool describe_shape = true,
                           bool describe_color = true)
        : SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT> (10),
          b_describe_shape_ (describe_shape),
          b_describe_color_ (describe_color)
      {
        feature_name_ = "SHOTColorEstimation";
      }
      
      /** \brief Empty destructor */
      ~SHOTColorEstimation () override = default;
 
      /** \brief Estimate the SHOT descriptor for a given point based on its spatial neighborhood of 3D points with normals
        * \param[in] index the index of the point in indices_
        * \param[in] indices the k-neighborhood point indices in surface_
        * \param[in] sqr_dists the k-neighborhood point distances in surface_
        * \param[out] shot the resultant SHOT descriptor representing the feature at the query point
        */
      void
      computePointSHOT (const int index,
                        const pcl::Indices &indices,
                        const std::vector<float> &sqr_dists,
                        Eigen::VectorXf &shot) override;
    protected:
      /** \brief Estimate the Signatures of Histograms of OrienTations (SHOT) descriptors at a set of points given by
        * <setInputCloud (), setIndices ()> using the surface in setSearchSurface () and the spatial locator in
        * setSearchMethod ()
        * \param output the resultant point cloud model dataset that contains the SHOT feature estimates
        */
      void
      computeFeature (pcl::PointCloud<PointOutT> &output) override;
 
      /** \brief Quadrilinear interpolation; used when color and shape descriptions are both activated
        * \param[in] indices the neighborhood point indices
        * \param[in] sqr_dists the neighborhood point distances
        * \param[in] index the index of the point in indices_
        * \param[out] binDistanceShape the resultant distance shape histogram
        * \param[out] binDistanceColor the resultant color shape histogram
        * \param[in] nr_bins_shape the number of bins in the shape histogram
        * \param[in] nr_bins_color the number of bins in the color histogram
        * \param[out] shot the resultant SHOT histogram
        */
      void
      interpolateDoubleChannel (const pcl::Indices &indices,
                                const std::vector<float> &sqr_dists,
                                const int index,
                                std::vector<double> &binDistanceShape,
                                std::vector<double> &binDistanceColor,
                                const int nr_bins_shape,
                                const int nr_bins_color,
                                Eigen::VectorXf &shot);
 
      /** \brief Compute shape descriptor. */
      bool b_describe_shape_;
 
      /** \brief Compute color descriptor. */
      bool b_describe_color_;
 
      /** \brief The number of bins in each color histogram. */
      int nr_color_bins_{30};
 
    public:
      /** \brief Converts RGB triplets to CIELab space.
        * \param[in] R the red channel
        * \param[in] G the green channel
        * \param[in] B the blue channel
        * \param[out] L the lightness
        * \param[out] A the first color-opponent dimension
        * \param[out] B2 the second color-opponent dimension
        */
      static void
      RGB2CIELAB (unsigned char R, unsigned char G, unsigned char B, float &L, float &A, float &B2);
 
      static std::array<float, 256> sRGB_LUT;
      static std::array<float, 4000> sXYZ_LUT;
  };
}
 
#ifdef PCL_NO_PRECOMPILE
#include <pcl/features/impl/shot.hpp>
#endif