radius_outlier_removal.hpp

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 * $Id: radius_outlier_removal.hpp 34685 2010-12-12 04:25:36Z rusu $
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#ifndef PCL_FILTERS_IMPL_RADIUS_OUTLIER_REMOVAL_H_
#define PCL_FILTERS_IMPL_RADIUS_OUTLIER_REMOVAL_H_

#include "pcl/filters/radius_outlier_removal.h"

template <typename PointT> void
pcl::RadiusOutlierRemoval<PointT>::applyFilter (PointCloud &output)
{
  if (search_radius_ == 0.0)
  {
    ROS_ERROR ("[pcl::%s::applyFilter] No radius defined!", getClassName ().c_str ());
    output.width = output.height = 0;
    output.points.clear ();
    return;
  }
  // Initialize the spatial locator
  //initTree (spatial_locator_type_, tree_, k_);

  // TODO: fix this
  tree_.reset (new KdTreeFLANN<PointT> ());

  // Send the input dataset to the spatial locator
  tree_->setInputCloud (input_);

  // Allocate enough space to hold the results
  std::vector<int> nn_indices (indices_->size ());
  std::vector<float> nn_dists (indices_->size ());

  output.points.resize (input_->points.size ());      // reserve enough space
  int nr_p = 0;
  // Go over all the points and check which doesn't have enough neighbors
  for (size_t cp = 0; cp < indices_->size (); ++cp)
  {
    int k = tree_->radiusSearch ((*indices_)[cp], search_radius_, nn_indices, nn_dists);
    // Check if the number of neighbors is larger than the user imposed limit
    if (k < min_pts_radius_)
      continue;

    output.points[nr_p++] = input_->points[(*indices_)[cp]];
  }
  output.points.resize (nr_p);
  output.width  = nr_p;
  output.height = 1;
  output.is_dense = true; // radiusSearch filters invalid points
}

#define PCL_INSTANTIATE_RadiusOutlierRemoval(T) template class pcl::RadiusOutlierRemoval<T>;

#endif    // PCL_FILTERS_IMPL_RADIUS_OUTLIER_REMOVAL_H_

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