registration.h

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/*
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 * $Id: registration.h 35947 2011-02-10 22:59:47Z rusu $
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#ifndef PCL_REGISTRATION_H_
#define PCL_REGISTRATION_H_

#include <boost/function.hpp>
#include <boost/bind.hpp>

// PCL includes
#include <pcl/pcl_base.h>

#include "pcl/kdtree/kdtree.h"
#include "pcl/kdtree/kdtree_flann.h"

#include "pcl/registration/transforms.h"

#include <Eigen/SVD>

#include "pcl/win32_macros.h"

namespace pcl
{
  template <typename PointSource, typename PointTarget> inline void 
  estimateRigidTransformationSVD (const pcl::PointCloud<PointSource> &cloud_src, 
                                  const pcl::PointCloud<PointTarget> &cloud_tgt, 
                                  Eigen::Matrix4f &transformation_matrix);

  template <typename PointSource, typename PointTarget> inline void 
  estimateRigidTransformationSVD (const pcl::PointCloud<PointSource> &cloud_src, const std::vector<int> &indices_src, 
                                  const pcl::PointCloud<PointTarget> &cloud_tgt, 
                                  Eigen::Matrix4f &transformation_matrix);

  template <typename PointSource, typename PointTarget> inline void 
  estimateRigidTransformationSVD (const pcl::PointCloud<PointSource> &cloud_src, const std::vector<int> &indices_src, 
                                  const pcl::PointCloud<PointTarget> &cloud_tgt, const std::vector<int> &indices_tgt, 
                                  Eigen::Matrix4f &transformation_matrix);


  template <typename PointSource, typename PointTarget>
  class Registration : public PCLBase<PointSource>
  {
    class FeatureContainerInterface;

    public:
      using PCLBase<PointSource>::initCompute;
      using PCLBase<PointSource>::deinitCompute;
      using PCLBase<PointSource>::input_;
      using PCLBase<PointSource>::indices_;

      typedef typename pcl::KdTree<PointTarget> KdTree;
      typedef typename pcl::KdTree<PointTarget>::Ptr KdTreePtr;
     
      typedef pcl::PointCloud<PointSource> PointCloudSource;
      typedef typename PointCloudSource::Ptr PointCloudSourcePtr;
      typedef typename PointCloudSource::ConstPtr PointCloudSourceConstPtr;

      typedef pcl::PointCloud<PointTarget> PointCloudTarget;
      typedef typename PointCloudTarget::Ptr PointCloudTargetPtr;
      typedef typename PointCloudTarget::ConstPtr PointCloudTargetConstPtr;

      typedef typename KdTree::PointRepresentationConstPtr PointRepresentationConstPtr;

      typedef std::map<std::string, boost::shared_ptr<FeatureContainerInterface> > FeaturesMap;

      Registration () : target_ (),
                        final_transformation_ (Eigen::Matrix4f::Identity ()),
                        transformation_ (Eigen::Matrix4f::Identity ()),
                        previous_transformation_ (Eigen::Matrix4f::Identity ()),
                        transformation_epsilon_ (0.0), corr_dist_threshold_ (std::numeric_limits<double>::max ()),
                        inlier_threshold_ (0.05),
                        converged_ (false), min_number_correspondences_ (3), /*k_ (1),*/ point_representation_ ()
      {
        tree_ = boost::make_shared<pcl::KdTreeFLANN<PointTarget> > ();     // ANN tree for nearest neighbor search
      }

      virtual inline void 
      setInputTarget (const PointCloudTargetConstPtr &cloud);

      inline PointCloudTargetConstPtr const 
      getInputTarget () { return (target_ ); }

      template <typename FeatureType> inline void 
      setSourceFeature (const typename pcl::PointCloud<FeatureType>::ConstPtr &source_feature, std::string key);

      template <typename FeatureType> inline typename pcl::PointCloud<FeatureType>::ConstPtr 
      getSourceFeature (std::string key);

      template <typename FeatureType> inline void 
      setTargetFeature (const typename pcl::PointCloud<FeatureType>::ConstPtr &target_feature, std::string key);

      template <typename FeatureType> inline typename pcl::PointCloud<FeatureType>::ConstPtr 
      getTargetFeature (std::string key);

      template <typename FeatureType> inline void 
      setRadiusSearch (const typename pcl::KdTree<FeatureType>::Ptr &tree, float r, std::string key);

      template <typename FeatureType> inline void 
      setKSearch (const typename pcl::KdTree<FeatureType>::Ptr &tree, int k, std::string key);

      inline Eigen::Matrix4f 
      getFinalTransformation () { return (final_transformation_); }

      inline Eigen::Matrix4f 
      getLastIncrementalTransformation () { return (transformation_); }

      inline void 
      setMaximumIterations (int nr_iterations) { max_iterations_ = nr_iterations; }

      inline int 
      getMaximumIterations () { return (max_iterations_); }

      inline void 
      setRANSACOutlierRejectionThreshold (double inlier_threshold) { inlier_threshold_ = inlier_threshold; }

      inline double 
      getRANSACOutlierRejectionThreshold () { return (inlier_threshold_); }

      inline void 
      setMaxCorrespondenceDistance (double distance_threshold) { corr_dist_threshold_ = distance_threshold; }

      inline double 
      getMaxCorrespondenceDistance () { return (corr_dist_threshold_); }

      inline void 
      setTransformationEpsilon (double epsilon) { transformation_epsilon_ = epsilon; }

      inline double 
      getTransformationEpsilon () { return (transformation_epsilon_); }

      inline void
      setPointRepresentation (const PointRepresentationConstPtr &point_representation)
      {
        point_representation_ = point_representation;
      }

      inline double 
      getFitnessScore (double max_range = std::numeric_limits<double>::max ());

      inline bool 
      hasConverged () { return (converged_); }

      inline void 
      align (PointCloudSource &output);

    protected:
      std::string reg_name_;

      KdTreePtr tree_;

      int nr_iterations_;

      int max_iterations_;

      PointCloudTargetConstPtr target_;

      Eigen::Matrix4f final_transformation_;

      Eigen::Matrix4f transformation_;

      Eigen::Matrix4f previous_transformation_;

      double transformation_epsilon_;

      double corr_dist_threshold_;

      double inlier_threshold_;

      bool converged_;

      int min_number_correspondences_;

      inline bool
      searchForNeighbors (const PointCloudSource &cloud, int index, 
                          std::vector<int> &indices, std::vector<float> &distances)
      {
        int k = tree_->nearestKSearch (cloud, index, 1, indices, distances);
        if (k == 0)
          return (false);
        return (true);
      }

      inline bool 
      hasValidFeatures ();

      inline void 
      findFeatureCorrespondences (int index, std::vector<int> &correspondence_indices);

      inline const std::string& 
      getClassName () const { return (reg_name_); }

    private:
 
      virtual void 
      computeTransformation (PointCloudSource &output) = 0;

      // /** \brief The number of K nearest neighbors to use for each point. */
      // int k_;

      PointRepresentationConstPtr point_representation_;

      FeaturesMap features_map_;


      template <typename FeatureType>
      class FeatureContainer : public pcl::Registration<PointSource, PointTarget>::FeatureContainerInterface
      {
        public:
          typedef typename pcl::PointCloud<FeatureType>::ConstPtr FeatureCloudConstPtr;
          typedef typename pcl::KdTree<FeatureType> KdTree;
          typedef typename pcl::KdTree<FeatureType>::Ptr KdTreePtr;
          typedef boost::function<int (const pcl::PointCloud<FeatureType> &, int, std::vector<int> &, 
                                        std::vector<float> &)> SearchMethod;
          
          FeatureContainer () : k_(0), radius_(0) {}

          void setSourceFeature (const FeatureCloudConstPtr &source_features)
          {
            source_features_ = source_features;
          }
          
          FeatureCloudConstPtr getSourceFeature ()
          {
            return (source_features_);
          }
          
          void setTargetFeature (const FeatureCloudConstPtr &target_features)
          {
            target_features_ = target_features;
            if (tree_)
            {
              tree_->setInputCloud (target_features_);
            }
          }
          
          FeatureCloudConstPtr getTargetFeature ()
          {
            return (target_features_);
          }
          
          void setRadiusSearch (KdTreePtr tree, float r)
          {
            tree_ = tree;
            radius_ = r;
            k_ = 0;
            if (target_features_)
            {
              tree_->setInputCloud (target_features_);
            }
          }

          void setKSearch (KdTreePtr tree, int k)
          {
            tree_ = tree;
            k_ = k;
            radius_ = 0.0;
            if (target_features_)
            {
              tree_->setInputCloud (target_features_);
            }
          }
          
          virtual bool isValid ()
          {
            if (!source_features_ || !target_features_ || !tree_)
            {
              return (false);
            }
            else
            {
              return (source_features_->points.size () > 0 && 
                      target_features_->points.size () > 0 &&
                      (k_ > 0 || radius_ > 0.0));
            }
          }

          virtual void findFeatureCorrespondences (int index, std::vector<int> &correspondence_indices, 
                                                   std::vector<float> &distances)
          {
            if (k_ > 0)
            {
              correspondence_indices.resize (k_);
              distances.resize (k_);
              tree_->nearestKSearch (*source_features_, index, k_, correspondence_indices, distances);
            }
            else
            {
              tree_->radiusSearch (*source_features_, index, radius_, correspondence_indices, distances);
            }
          }
          
        private:
          FeatureCloudConstPtr source_features_, target_features_;
          KdTreePtr tree_;
          SearchMethod search_method_;
          int k_;
          double radius_;
      };

      class FeatureContainerInterface
      {
        public:
          virtual bool isValid () = 0;
          virtual void findFeatureCorrespondences (int index, std::vector<int> &correspondence_indices, 
                                                   std::vector<float> &distances) = 0;
      };

   };
}

#include "pcl/registration/registration.hpp"

#endif  //#ifndef PCL_REGISTRATION_H_

---

pcl
Author(s): See http://pcl.ros.org/authors for the complete list of authors.
autogenerated on Fri Jan 11 09:55:23 2013