correspondence_estimation.h

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#pragma once
 
#include <string>
 
#include <pcl/pcl_base.h>
#include <pcl/common/io.h> // for getFields
#include <pcl/search/kdtree.h>
#include <pcl/memory.h>
#include <pcl/pcl_macros.h>
 
#include <pcl/registration/correspondence_types.h>
 
namespace pcl
{
  namespace registration
  {
    /** \brief Abstract @b CorrespondenceEstimationBase class. 
      * All correspondence estimation methods should inherit from this.
      * \author Radu B. Rusu
      * \ingroup registration
      */
    template <typename PointSource, typename PointTarget, typename Scalar = float>
    class CorrespondenceEstimationBase: public PCLBase<PointSource>
    {
      public:
        using Ptr = shared_ptr<CorrespondenceEstimationBase<PointSource, PointTarget, Scalar> >;
        using ConstPtr = shared_ptr<const CorrespondenceEstimationBase<PointSource, PointTarget, Scalar> >;
 
        // using PCLBase<PointSource>::initCompute;
        using PCLBase<PointSource>::deinitCompute;
        using PCLBase<PointSource>::input_;
        using PCLBase<PointSource>::indices_;
        using PCLBase<PointSource>::setIndices;
 
        using KdTree = pcl::search::KdTree<PointTarget>;
        using KdTreePtr = typename KdTree::Ptr;
 
        using KdTreeReciprocal = pcl::search::KdTree<PointSource>;
        using KdTreeReciprocalPtr = typename KdTree::Ptr;
 
        using PointCloudSource = pcl::PointCloud<PointSource>;
        using PointCloudSourcePtr = typename PointCloudSource::Ptr;
        using PointCloudSourceConstPtr = typename PointCloudSource::ConstPtr;
 
        using PointCloudTarget = pcl::PointCloud<PointTarget>;
        using PointCloudTargetPtr = typename PointCloudTarget::Ptr;
        using PointCloudTargetConstPtr = typename PointCloudTarget::ConstPtr;
 
        using PointRepresentationConstPtr = typename KdTree::PointRepresentationConstPtr;
 
        /** \brief Empty constructor. */
        CorrespondenceEstimationBase () 
          : corr_name_ ("CorrespondenceEstimationBase")
          , tree_ (new pcl::search::KdTree<PointTarget>)
          , tree_reciprocal_ (new pcl::search::KdTree<PointSource>)
          , target_ ()
          , point_representation_ ()
          , input_transformed_ ()
          , target_cloud_updated_ (true)
          , source_cloud_updated_ (true)
          , force_no_recompute_ (false)
          , force_no_recompute_reciprocal_ (false)
        {
        }
      
        /** \brief Empty destructor */
        ~CorrespondenceEstimationBase () {}
 
        /** \brief Provide a pointer to the input source 
          * (e.g., the point cloud that we want to align to the target)
          *
          * \param[in] cloud the input point cloud source
          */
        inline void 
        setInputSource (const PointCloudSourceConstPtr &cloud)
        {
          source_cloud_updated_ = true;
          PCLBase<PointSource>::setInputCloud (cloud);
          input_fields_ = pcl::getFields<PointSource> ();
        }
 
        /** \brief Get a pointer to the input point cloud dataset target. */
        inline PointCloudSourceConstPtr const 
        getInputSource () 
        { 
          return (input_ ); 
        }
 
        /** \brief Provide a pointer to the input target 
          * (e.g., the point cloud that we want to align the input source to)
          * \param[in] cloud the input point cloud target
          */
        inline void 
        setInputTarget (const PointCloudTargetConstPtr &cloud);
 
        /** \brief Get a pointer to the input point cloud dataset target. */
        inline PointCloudTargetConstPtr const 
        getInputTarget () { return (target_ ); }
 
 
        /** \brief See if this rejector requires source normals */
        virtual bool
        requiresSourceNormals () const
        { return (false); }
 
        /** \brief Abstract method for setting the source normals */
        virtual void
        setSourceNormals (pcl::PCLPointCloud2::ConstPtr /*cloud2*/)
        {
          PCL_WARN ("[pcl::registration::%s::setSourceNormals] This class does not require input source normals", getClassName ().c_str ());
        }
        
        /** \brief See if this rejector requires target normals */
        virtual bool
        requiresTargetNormals () const
        { return (false); }
 
        /** \brief Abstract method for setting the target normals */
        virtual void
        setTargetNormals (pcl::PCLPointCloud2::ConstPtr /*cloud2*/)
        {
          PCL_WARN ("[pcl::registration::%s::setTargetNormals] This class does not require input target normals", getClassName ().c_str ());
        }
 
        /** \brief Provide a pointer to the vector of indices that represent the 
          * input source point cloud.
          * \param[in] indices a pointer to the vector of indices 
          */
        inline void
        setIndicesSource (const IndicesPtr &indices)
        {
          setIndices (indices);
        }
 
        /** \brief Get a pointer to the vector of indices used for the source dataset. */
        inline IndicesPtr const 
        getIndicesSource () { return (indices_); }
 
        /** \brief Provide a pointer to the vector of indices that represent the input target point cloud.
          * \param[in] indices a pointer to the vector of indices 
          */
        inline void
        setIndicesTarget (const IndicesPtr &indices)
        {
          target_cloud_updated_ = true;
          target_indices_ = indices;
        }
 
        /** \brief Get a pointer to the vector of indices used for the target dataset. */
        inline IndicesPtr const 
        getIndicesTarget () { return (target_indices_); }
 
        /** \brief Provide a pointer to the search object used to find correspondences in
          * the target cloud.
          * \param[in] tree a pointer to the spatial search object.
          * \param[in] force_no_recompute If set to true, this tree will NEVER be 
          * recomputed, regardless of calls to setInputTarget. Only use if you are 
          * confident that the tree will be set correctly.
          */
        inline void
        setSearchMethodTarget (const KdTreePtr &tree, 
                               bool force_no_recompute = false) 
        { 
          tree_ = tree; 
          if (force_no_recompute)
          {
            force_no_recompute_ = true;
          }
          // Since we just set a new tree, we need to check for updates
          target_cloud_updated_ = true;
        }
 
        /** \brief Get a pointer to the search method used to find correspondences in the
          * target cloud. */
        inline KdTreePtr
        getSearchMethodTarget () const
        {
          return (tree_);
        }
 
        /** \brief Provide a pointer to the search object used to find correspondences in
          * the source cloud (usually used by reciprocal correspondence finding).
          * \param[in] tree a pointer to the spatial search object.
          * \param[in] force_no_recompute If set to true, this tree will NEVER be 
          * recomputed, regardless of calls to setInputSource. Only use if you are 
          * extremely confident that the tree will be set correctly.
          */
        inline void
        setSearchMethodSource (const KdTreeReciprocalPtr &tree, 
                               bool force_no_recompute = false) 
        { 
          tree_reciprocal_ = tree; 
          if ( force_no_recompute )
          {
            force_no_recompute_reciprocal_ = true;
          }
          // Since we just set a new tree, we need to check for updates
          source_cloud_updated_ = true;
        }
 
        /** \brief Get a pointer to the search method used to find correspondences in the
          * source cloud. */
        inline KdTreeReciprocalPtr
        getSearchMethodSource () const
        {
          return (tree_reciprocal_);
        }
 
        /** \brief Determine the correspondences between input and target cloud.
          * \param[out] correspondences the found correspondences (index of query point, index of target point, distance)
          * \param[in] max_distance maximum allowed distance between correspondences
          */
        virtual void 
        determineCorrespondences (pcl::Correspondences &correspondences,
                                  double max_distance = std::numeric_limits<double>::max ()) = 0;
 
        /** \brief Determine the reciprocal correspondences between input and target cloud.
          * A correspondence is considered reciprocal if both Src_i has Tgt_i as a 
          * correspondence, and Tgt_i has Src_i as one.
          *
          * \param[out] correspondences the found correspondences (index of query and target point, distance)
          * \param[in] max_distance maximum allowed distance between correspondences
          */
        virtual void 
        determineReciprocalCorrespondences (pcl::Correspondences &correspondences,
                                            double max_distance = std::numeric_limits<double>::max ()) = 0;
 
        /** \brief Provide a boost shared pointer to the PointRepresentation to be used 
          * when searching for nearest neighbors.
          *
          * \param[in] point_representation the PointRepresentation to be used by the 
          * k-D tree for nearest neighbor search
          */
        inline void
        setPointRepresentation (const PointRepresentationConstPtr &point_representation)
        {
          point_representation_ = point_representation;
        }
 
        /** \brief Clone and cast to CorrespondenceEstimationBase */
        virtual typename CorrespondenceEstimationBase<PointSource, PointTarget, Scalar>::Ptr clone () const = 0;
 
      protected:
        /** \brief The correspondence estimation method name. */
        std::string corr_name_;
 
        /** \brief A pointer to the spatial search object used for the target dataset. */
        KdTreePtr tree_;
 
        /** \brief A pointer to the spatial search object used for the source dataset. */
        KdTreeReciprocalPtr tree_reciprocal_;
 
 
        
        /** \brief The input point cloud dataset target. */
        PointCloudTargetConstPtr target_;
 
        /** \brief The target point cloud dataset indices. */
        IndicesPtr target_indices_;
 
        /** \brief The point representation used (internal). */
        PointRepresentationConstPtr point_representation_;
 
        /** \brief The transformed input source point cloud dataset. */
        PointCloudTargetPtr input_transformed_;
 
        /** \brief The types of input point fields available. */
        std::vector<pcl::PCLPointField> input_fields_;
 
        /** \brief Abstract class get name method. */
        inline const std::string& 
        getClassName () const { return (corr_name_); }
 
        /** \brief Internal computation initialization. */
        bool
        initCompute ();
        
        /** \brief Internal computation initialization for reciprocal correspondences. */
        bool
        initComputeReciprocal ();
 
        /** \brief Variable that stores whether we have a new target cloud, meaning we need to pre-process it again.
         * This way, we avoid rebuilding the kd-tree for the target cloud every time the determineCorrespondences () method
         * is called. */
        bool target_cloud_updated_;
        /** \brief Variable that stores whether we have a new source cloud, meaning we need to pre-process it again.
         * This way, we avoid rebuilding the reciprocal kd-tree for the source cloud every time the determineCorrespondences () method
         * is called. */
        bool source_cloud_updated_;
        /** \brief A flag which, if set, means the tree operating on the target cloud 
         * will never be recomputed*/
        bool force_no_recompute_;
        
        /** \brief A flag which, if set, means the tree operating on the source cloud 
         * will never be recomputed*/
        bool force_no_recompute_reciprocal_;
 
     };
 
    /** \brief @b CorrespondenceEstimation represents the base class for
      * determining correspondences between target and query point
      * sets/features.
      *
      * Code example:
      *
      * \code
      * pcl::PointCloud<pcl::PointXYZRGBA>::Ptr source, target;
      * // ... read or fill in source and target
      * pcl::CorrespondenceEstimation<pcl::PointXYZ, pcl::PointXYZ> est;
      * est.setInputSource (source);
      * est.setInputTarget (target);
      *
      * pcl::Correspondences all_correspondences;
      * // Determine all reciprocal correspondences
      * est.determineReciprocalCorrespondences (all_correspondences);
      * \endcode
      *
      * \author Radu B. Rusu, Michael Dixon, Dirk Holz
      * \ingroup registration
      */
    template <typename PointSource, typename PointTarget, typename Scalar = float>
    class CorrespondenceEstimation : public CorrespondenceEstimationBase<PointSource, PointTarget, Scalar>
    {
      public:
        using Ptr = shared_ptr<CorrespondenceEstimation<PointSource, PointTarget, Scalar> >;
        using ConstPtr = shared_ptr<const CorrespondenceEstimation<PointSource, PointTarget, Scalar> >;
 
        using CorrespondenceEstimationBase<PointSource, PointTarget, Scalar>::point_representation_;
        using CorrespondenceEstimationBase<PointSource, PointTarget, Scalar>::input_transformed_;
        using CorrespondenceEstimationBase<PointSource, PointTarget, Scalar>::tree_;
        using CorrespondenceEstimationBase<PointSource, PointTarget, Scalar>::tree_reciprocal_;
        using CorrespondenceEstimationBase<PointSource, PointTarget, Scalar>::target_;
        using CorrespondenceEstimationBase<PointSource, PointTarget, Scalar>::corr_name_;
        using CorrespondenceEstimationBase<PointSource, PointTarget, Scalar>::target_indices_;
        using CorrespondenceEstimationBase<PointSource, PointTarget, Scalar>::getClassName;
        using CorrespondenceEstimationBase<PointSource, PointTarget, Scalar>::initCompute;
        using CorrespondenceEstimationBase<PointSource, PointTarget, Scalar>::initComputeReciprocal;
        using CorrespondenceEstimationBase<PointSource, PointTarget, Scalar>::input_;
        using CorrespondenceEstimationBase<PointSource, PointTarget, Scalar>::indices_;
        using CorrespondenceEstimationBase<PointSource, PointTarget, Scalar>::input_fields_;
        using PCLBase<PointSource>::deinitCompute;
 
        using KdTree = pcl::search::KdTree<PointTarget>;
        using KdTreePtr = typename KdTree::Ptr;
 
        using PointCloudSource = pcl::PointCloud<PointSource>;
        using PointCloudSourcePtr = typename PointCloudSource::Ptr;
        using PointCloudSourceConstPtr = typename PointCloudSource::ConstPtr;
 
        using PointCloudTarget = pcl::PointCloud<PointTarget>;
        using PointCloudTargetPtr = typename PointCloudTarget::Ptr;
        using PointCloudTargetConstPtr = typename PointCloudTarget::ConstPtr;
 
        using PointRepresentationConstPtr = typename KdTree::PointRepresentationConstPtr;
 
        /** \brief Empty constructor. */
        CorrespondenceEstimation () 
        {
          corr_name_  = "CorrespondenceEstimation";
        }
      
        /** \brief Empty destructor */
        ~CorrespondenceEstimation () {}
 
        /** \brief Determine the correspondences between input and target cloud.
          * \param[out] correspondences the found correspondences (index of query point, index of target point, distance)
          * \param[in] max_distance maximum allowed distance between correspondences
          */
        void 
        determineCorrespondences (pcl::Correspondences &correspondences,
                                  double max_distance = std::numeric_limits<double>::max ()) override;
 
        /** \brief Determine the reciprocal correspondences between input and target cloud.
          * A correspondence is considered reciprocal if both Src_i has Tgt_i as a 
          * correspondence, and Tgt_i has Src_i as one.
          *
          * \param[out] correspondences the found correspondences (index of query and target point, distance)
          * \param[in] max_distance maximum allowed distance between correspondences
          */
        void 
        determineReciprocalCorrespondences (pcl::Correspondences &correspondences,
                                            double max_distance = std::numeric_limits<double>::max ()) override;
 
        
        /** \brief Clone and cast to CorrespondenceEstimationBase */
        typename CorrespondenceEstimationBase<PointSource, PointTarget, Scalar>::Ptr
        clone () const override
        {
          Ptr copy (new CorrespondenceEstimation<PointSource, PointTarget, Scalar> (*this));
          return (copy);
        }
     };
  }
}
 
#include <pcl/registration/impl/correspondence_estimation.hpp>