poisson.h

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#pragma once
 
#include <pcl/memory.h>
#include <pcl/pcl_macros.h>
#include <pcl/surface/reconstruction.h>
 
namespace pcl
{
  namespace poisson
  {
    class CoredVectorMeshData;
    template <class Real> struct Point3D;
  }
 
  /** \brief The Poisson surface reconstruction algorithm.
    * \note Code adapted from Misha Kazhdan: http://www.cs.jhu.edu/~misha/Code/PoissonRecon/
    * \note Based on the paper:
    *       * Michael Kazhdan, Matthew Bolitho, Hugues Hoppe, "Poisson surface reconstruction",
    *         SGP '06 Proceedings of the fourth Eurographics symposium on Geometry processing
    * \author Alexandru-Eugen Ichim
    * \ingroup surface
    */
  template<typename PointNT>
  class Poisson : public SurfaceReconstruction<PointNT>
  {
    public:
      using Ptr = shared_ptr<Poisson<PointNT> >;
      using ConstPtr = shared_ptr<const Poisson<PointNT> >;
 
      using SurfaceReconstruction<PointNT>::input_;
      using SurfaceReconstruction<PointNT>::tree_;
 
      using PointCloudPtr = typename pcl::PointCloud<PointNT>::Ptr;
 
      using KdTree = pcl::KdTree<PointNT>;
      using KdTreePtr = typename KdTree::Ptr;
 
      /** \brief Constructor that sets all the parameters to working default values. */
      Poisson ();
 
      /** \brief Destructor. */
      ~Poisson () override;
 
      /** \brief Create the surface.
        * \param[out] output the resultant polygonal mesh
        */
      void
      performReconstruction (pcl::PolygonMesh &output) override;
 
      /** \brief Create the surface.
        * \param[out] points the vertex positions of the resulting mesh
        * \param[out] polygons the connectivity of the resulting mesh
        */
      void
      performReconstruction (pcl::PointCloud<PointNT> &points,
                             std::vector<pcl::Vertices> &polygons) override;
 
      /** \brief Set the maximum depth of the tree that will be used for surface reconstruction.
        * \note Running at depth d corresponds to solving on a voxel grid whose resolution is no larger than
        * 2^d x 2^d x 2^d. Note that since the reconstructor adapts the octree to the sampling density, the specified
        * reconstruction depth is only an upper bound.
        * \param[in] depth the depth parameter
        */
      inline void
      setDepth (int depth) { depth_ = depth; }
 
      /** \brief Get the depth parameter */
      inline int
      getDepth () { return depth_; }
 
      inline void
      setMinDepth (int min_depth) { min_depth_ = min_depth; }
 
      inline int
      getMinDepth () { return min_depth_; }
 
      inline void
      setPointWeight (float point_weight) { point_weight_ = point_weight; }
 
      inline float
      getPointWeight () { return point_weight_; }
 
      /** \brief Set the ratio between the diameter of the cube used for reconstruction and the diameter of the
        * samples' bounding cube.
        * \param[in] scale the given parameter value
        */
      inline void
      setScale (float scale) { scale_ = scale; }
 
      /** Get the ratio between the diameter of the cube used for reconstruction and the diameter of the
        * samples' bounding cube.
        */
      inline float
      getScale () { return scale_; }
 
      /** \brief Set the the depth at which a block Gauss-Seidel solver is used to solve the Laplacian equation
        * \note Using this parameter helps reduce the memory overhead at the cost of a small increase in
        * reconstruction time. (In practice, we have found that for reconstructions of depth 9 or higher a subdivide
        * depth of 7 or 8 can greatly reduce the memory usage.)
        * \param[in] solver_divide the given parameter value
        */
      inline void
      setSolverDivide (int solver_divide) { solver_divide_ = solver_divide; }
 
      /** \brief Get the depth at which a block Gauss-Seidel solver is used to solve the Laplacian equation */
      inline int
      getSolverDivide () { return solver_divide_; }
 
      /** \brief Set the depth at which a block iso-surface extractor should be used to extract the iso-surface
        * \note Using this parameter helps reduce the memory overhead at the cost of a small increase in extraction
        * time. (In practice, we have found that for reconstructions of depth 9 or higher a subdivide depth of 7 or 8
        * can greatly reduce the memory usage.)
        * \param[in] iso_divide the given parameter value
        */
      inline void
      setIsoDivide (int iso_divide) { iso_divide_ = iso_divide; }
 
      /** \brief Get the depth at which a block iso-surface extractor should be used to extract the iso-surface */
      inline int
      getIsoDivide () { return iso_divide_; }
 
      /** \brief Set the minimum number of sample points that should fall within an octree node as the octree
        * construction is adapted to sampling density
        * \note For noise-free samples, small values in the range [1.0 - 5.0] can be used. For more noisy samples,
        * larger values in the range [15.0 - 20.0] may be needed to provide a smoother, noise-reduced, reconstruction.
        * \param[in] samples_per_node the given parameter value
        */
      inline void
      setSamplesPerNode (float samples_per_node) { samples_per_node_ = samples_per_node; }
 
      /** \brief Get the minimum number of sample points that should fall within an octree node as the octree
        * construction is adapted to sampling density
        */
      inline float
      getSamplesPerNode () { return samples_per_node_; }
 
      /** \brief Set the confidence flag
        * \note Enabling this flag tells the reconstructor to use the size of the normals as confidence information.
        * When the flag is not enabled, all normals are normalized to have unit-length prior to reconstruction.
        * \param[in] confidence the given flag
        */
      inline void
      setConfidence (bool confidence) { confidence_ = confidence; }
 
      /** \brief Get the confidence flag */
      inline bool
      getConfidence () { return confidence_; }
 
      /** \brief Enabling this flag tells the reconstructor to output a polygon mesh (rather than triangulating the
        * results of Marching Cubes).
        * \param[in] output_polygons the given flag
        */
      inline void
      setOutputPolygons (bool output_polygons) { output_polygons_ = output_polygons; }
 
      /** \brief Get whether the algorithm outputs a polygon mesh or a triangle mesh */
      inline bool
      getOutputPolygons () { return output_polygons_; }
 
      /** \brief Set the degree parameter
        * \param[in] degree the given degree
        */
      inline void
      setDegree (int degree) { degree_ = degree; }
 
      /** \brief Get the degree parameter */
      inline int
      getDegree () { return degree_; }
 
      /** \brief Set the manifold flag.
        * \note Enabling this flag tells the reconstructor to add the polygon barycenter when triangulating polygons
        * with more than three vertices.
        * \param[in] manifold the given flag
        */
      inline void
      setManifold (bool manifold) { manifold_ = manifold; }
 
      /** \brief Get the manifold flag */
      inline bool
      getManifold () { return manifold_; }
 
      /** \brief Set the number of threads to use.
       * \param[in] threads the number of threads
       */
      void
      setThreads(int threads);
      
 
      /** \brief Get the number of threads*/
      inline int
      getThreads()
      {
        return threads_;
      }
 
    protected:
      /** \brief Class get name method. */
      std::string
      getClassName () const override { return ("Poisson"); }
 
    private:
      int depth_{8};
      int min_depth_{5};
      float point_weight_{4};
      float scale_{1.1f};
      int solver_divide_{8};
      int iso_divide_{8};
      float samples_per_node_{1.0};
      bool confidence_{false};
      bool output_polygons_{false};
 
      bool no_reset_samples_{false};
      bool no_clip_tree_{false};
      bool manifold_{true};
 
      int refine_{3};
      int kernel_depth_{8};
      int degree_{2};
      bool non_adaptive_weights_{false};
      bool show_residual_{false};
      int min_iterations_{8};
      float solver_accuracy_{1e-3f};
      int threads_{1};
 
      template<int Degree> void
      execute (poisson::CoredVectorMeshData &mesh,
               poisson::Point3D<float> &translate,
               float &scale);
 
    public:
      PCL_MAKE_ALIGNED_OPERATOR_NEW
  };
}
 
#ifdef PCL_NO_PRECOMPILE
#include <pcl/surface/impl/poisson.hpp>
#endif