correspondence_estimation.hpp

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#ifndef PCL_REGISTRATION_IMPL_CORRESPONDENCE_ESTIMATION_H_
#define PCL_REGISTRATION_IMPL_CORRESPONDENCE_ESTIMATION_H_

#include <pcl/common/concatenate.h>
//#include <pcl/registration/correspondence_estimation.h>

template <typename PointSource, typename PointTarget> inline void
pcl::registration::CorrespondenceEstimation<PointSource, PointTarget>::setInputTarget (
    const PointCloudTargetConstPtr &cloud)
{
  if (cloud->points.empty ())
  {
    PCL_ERROR ("[pcl::%s::setInputTarget] Invalid or empty point cloud dataset given!\n", getClassName ().c_str ());
    return;
  }
  target_ = cloud;
  tree_->setInputCloud (target_);
}

template <typename PointSource, typename PointTarget> void
pcl::registration::CorrespondenceEstimation<PointSource, PointTarget>::determineCorrespondences (
    pcl::Correspondences &correspondences, float max_distance)
{
  typedef typename pcl::traits::fieldList<PointTarget>::type FieldListTarget;

  if (!initCompute ())
    return;

  if (!target_)
  {
    PCL_WARN ("[pcl::%s::compute] No input target dataset was given!\n", getClassName ().c_str ());
    return;
  }

  float max_dist_sqr = max_distance * max_distance;

  correspondences.resize (indices_->size ());
  std::vector<int> index (1);
  std::vector<float> distance (1);
  pcl::Correspondence corr;
  for (size_t i = 0; i < indices_->size (); ++i)
  {
    // Copy the source data to a target PointTarget format so we can search in the tree
    PointTarget pt;
    pcl::for_each_type <FieldListTarget> (pcl::NdConcatenateFunctor <PointSource, PointTarget> (
          input_->points[(*indices_)[i]], 
          pt));

    //if (tree_->nearestKSearch (input_->points[(*indices_)[i]], 1, index, distance))
    if (tree_->nearestKSearch (pt, 1, index, distance))
    {
      if (distance[0] <= max_dist_sqr)
      {
        corr.index_query = static_cast<int> (i);
        corr.index_match = index[0];
        corr.distance = distance[0];
        correspondences[i] = corr;
        continue;
      }
    }
//    correspondences[i] = pcl::Correspondence(i, -1, std::numeric_limits<float>::max());
  }
  deinitCompute ();
}

template <typename PointSource, typename PointTarget> void
pcl::registration::CorrespondenceEstimation<PointSource, PointTarget>::determineReciprocalCorrespondences (
    pcl::Correspondences &correspondences)
{
  typedef typename pcl::traits::fieldList<PointSource>::type FieldListSource;
  typedef typename pcl::traits::fieldList<PointTarget>::type FieldListTarget;
  typedef typename pcl::intersect<FieldListSource, FieldListTarget>::type FieldList;
  
  if (!initCompute ())
    return;

  if (!target_)
  {
    PCL_WARN ("[pcl::%s::compute] No input target dataset was given!\n", getClassName ().c_str ());
    return;
  }

  // setup tree for reciprocal search
  pcl::KdTreeFLANN<PointSource> tree_reciprocal;
  tree_reciprocal.setInputCloud (input_, indices_);

  correspondences.resize (indices_->size());
  std::vector<int> index (1);
  std::vector<float> distance (1);
  std::vector<int> index_reciprocal (1);
  std::vector<float> distance_reciprocal (1);
  pcl::Correspondence corr;
  unsigned int nr_valid_correspondences = 0;

  for (size_t i = 0; i < indices_->size (); ++i)
  {
    // Copy the source data to a target PointTarget format so we can search in the tree
    PointTarget pt_src;
    pcl::for_each_type <FieldList> (pcl::NdConcatenateFunctor <PointSource, PointTarget> (
          input_->points[(*indices_)[i]], 
          pt_src));

    //tree_->nearestKSearch (input_->points[(*indices_)[i]], 1, index, distance);
    tree_->nearestKSearch (pt_src, 1, index, distance);

    // Copy the target data to a target PointSource format so we can search in the tree_reciprocal
    PointSource pt_tgt;
    pcl::for_each_type <FieldList> (pcl::NdConcatenateFunctor <PointTarget, PointSource> (
          target_->points[index[0]],
          pt_tgt));
    //tree_reciprocal.nearestKSearch (target_->points[index[0]], 1, index_reciprocal, distance_reciprocal);
    tree_reciprocal.nearestKSearch (pt_tgt, 1, index_reciprocal, distance_reciprocal);

    if ((*indices_)[i] == index_reciprocal[0])
    {
      corr.index_query = (*indices_)[i];
      corr.index_match = index[0];
      corr.distance = distance[0];
      correspondences[nr_valid_correspondences] = corr;
      ++nr_valid_correspondences;
    }
  }
  correspondences.resize (nr_valid_correspondences);

  deinitCompute ();
}

//#define PCL_INSTANTIATE_CorrespondenceEstimation(T,U) template class PCL_EXPORTS pcl::registration::CorrespondenceEstimation<T,U>;

#endif /* PCL_REGISTRATION_IMPL_CORRESPONDENCE_ESTIMATION_H_ */