registration.h

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 * $Id: registration.h 6133 2012-07-04 18:41:13Z 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/common/transforms.h>
#include <pcl/pcl_macros.h>
#include <pcl/kdtree/kdtree_flann.h>
#include <pcl/registration/transformation_estimation.h>

namespace pcl
{
  template <typename PointSource, typename PointTarget>
  class Registration : public PCLBase<PointSource>
  {
    public:
      using PCLBase<PointSource>::initCompute;
      using PCLBase<PointSource>::deinitCompute;
      using PCLBase<PointSource>::input_;
      using PCLBase<PointSource>::indices_;

      typedef boost::shared_ptr< Registration<PointSource, PointTarget> > Ptr;
      typedef boost::shared_ptr< const Registration<PointSource, PointTarget> > ConstPtr;

      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 typename pcl::registration::TransformationEstimation<PointSource, PointTarget> TransformationEstimation;
      typedef typename TransformationEstimation::Ptr TransformationEstimationPtr;
      typedef typename TransformationEstimation::ConstPtr TransformationEstimationConstPtr;

      Registration () : reg_name_ (),
                        tree_ (new pcl::KdTreeFLANN<PointTarget>),
                        nr_iterations_(0),
                        max_iterations_(10),
                        ransac_iterations_ (0),
                        target_ (),
                        final_transformation_ (Eigen::Matrix4f::Identity ()),
                        transformation_ (Eigen::Matrix4f::Identity ()),
                        previous_transformation_ (Eigen::Matrix4f::Identity ()),
                        transformation_epsilon_ (0.0), 
                        euclidean_fitness_epsilon_ (-std::numeric_limits<double>::max ()),
                        corr_dist_threshold_ (std::sqrt (std::numeric_limits<double>::max ())),
                        inlier_threshold_ (0.05),
                        converged_ (false), 
                        min_number_correspondences_ (3), 
                        correspondence_distances_ (),
                        transformation_estimation_ (),
                        update_visualizer_ (NULL),
                        point_representation_ ()
      {
      }

      virtual ~Registration () {}

      void
      setTransformationEstimation (const TransformationEstimationPtr &te) { transformation_estimation_ = te; }

      virtual inline void 
      setInputTarget (const PointCloudTargetConstPtr &cloud);

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

      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 
      setRANSACIterations (int ransac_iterations) { ransac_iterations_ = ransac_iterations; }

      inline double 
      getRANSACIterations () { return (ransac_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 
      setEuclideanFitnessEpsilon (double epsilon) { euclidean_fitness_epsilon_ = epsilon; }

      inline double 
      getEuclideanFitnessEpsilon () { return (euclidean_fitness_epsilon_); }

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

      template<typename FunctionSignature> inline bool
      registerVisualizationCallback (boost::function<FunctionSignature> &visualizerCallback)
      {
        if (visualizerCallback != NULL)
        {
          update_visualizer_ = visualizerCallback;
          return (true);
        }
        else
          return (false);
      }

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

      inline double 
      getFitnessScore (const std::vector<float> &distances_a, const std::vector<float> &distances_b);

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

      inline void 
      align (PointCloudSource &output);

      inline void 
      align (PointCloudSource &output, const Eigen::Matrix4f& guess);

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

    protected:
      std::string reg_name_;

      KdTreePtr tree_;

      int nr_iterations_;

      int max_iterations_;

      int ransac_iterations_;

      PointCloudTargetConstPtr target_;

      Eigen::Matrix4f final_transformation_;

      Eigen::Matrix4f transformation_;

      Eigen::Matrix4f previous_transformation_;

      double transformation_epsilon_;

      double euclidean_fitness_epsilon_;

      double corr_dist_threshold_;

      double inlier_threshold_;

      bool converged_;

      int min_number_correspondences_;

      std::vector<float> correspondence_distances_;                                                              

      TransformationEstimationPtr transformation_estimation_;

      boost::function<void(const pcl::PointCloud<PointSource> &cloud_src,
                           const std::vector<int> &indices_src,
                           const pcl::PointCloud<PointTarget> &cloud_tgt,
                           const std::vector<int> &indices_tgt)> update_visualizer_;

      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);
      }

    private:
 
      virtual void 
      computeTransformation (PointCloudSource &output, const Eigen::Matrix4f& guess) = 0;

      PointRepresentationConstPtr point_representation_;
    public:
      EIGEN_MAKE_ALIGNED_OPERATOR_NEW
   };
}

#include <pcl/registration/impl/registration.hpp>

#endif  //#ifndef PCL_REGISTRATION_H_