keypoint.hpp

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template <typename PointInT, typename PointOutT> inline void
  pcl::Keypoint<PointInT, PointOutT>::compute (PointCloudOut &output)
{
  if (!initCompute ())
  {
    ROS_ERROR ("[pcl::%s::compute] initCompute failed!", getClassName ().c_str ());
    return;
  }

  // Check if a space search locator was given
  if (!tree_)
  {
    ROS_ERROR ("[pcl::%s::compute] No spatial search method was given!", getClassName ().c_str ());
    return;
  }

  // If no search surface has been defined, use the input dataset as the search surface itself
  if (!surface_)
  {
    surface_ = input_;
  }

  // Send the surface dataset to the spatial locator
  tree_->setInputCloud (surface_);

  // Do a fast check to see if the search parameters are well defined
  if (search_radius_ != 0.0)
  {
    if (k_ != 0)
    {
      ROS_ERROR ("[pcl::%s::compute] Both radius (%f) and K (%d) defined! Set one of them to zero first and then re-run compute ().", getClassName ().c_str (), search_radius_, k_);
      return;
    }
    else                  // Use the radiusSearch () function
    {
      search_parameter_ = search_radius_;
      if (surface_ == input_)       // if the two surfaces are the same
      {
        // Declare the search locator definition
        int (KdTree::*radiusSearch)(int index, double radius, std::vector<int> &k_indices,
                                     std::vector<float> &k_distances, int max_nn) const = &KdTree::radiusSearch;
        search_method_ = boost::bind (radiusSearch, boost::ref (tree_), _1, _2, _3, _4, INT_MAX);
      }
      else
      {
        // Declare the search locator definition
        int (KdTree::*radiusSearchSurface)(const PointCloudIn &cloud, int index, double radius, std::vector<int> &k_indices,
                                            std::vector<float> &k_distances, int max_nn) const = &KdTree::radiusSearch;
        search_method_surface_ = boost::bind (radiusSearchSurface, boost::ref (tree_), _1, _2, _3, _4, _5, INT_MAX);
      }
    }
  }
  else
  {
    if (k_ != 0)         // Use the nearestKSearch () function
    {
      search_parameter_ = k_;
      if (surface_ == input_)       // if the two surfaces are the same
      {
        // Declare the search locator definition
        int (KdTree::*nearestKSearch)(int index, int k, std::vector<int> &k_indices, std::vector<float> &k_distances) = &KdTree::nearestKSearch;
        search_method_ = boost::bind (nearestKSearch, boost::ref (tree_), _1, _2, _3, _4);
      }
      else
      {
        // Declare the search locator definition
        int (KdTree::*nearestKSearchSurface)(const PointCloudIn &cloud, int index, int k, std::vector<int> &k_indices, std::vector<float> &k_distances) = &KdTree::nearestKSearch;
        search_method_surface_ = boost::bind (nearestKSearchSurface, boost::ref (tree_), _1, _2, _3, _4, _5);
      }
    }
    else
    {
      ROS_ERROR ("[pcl::%s::compute] Neither radius nor K defined! Set one of them to a positive number first and then re-run compute ().", getClassName ().c_str ());
      return;
    }
  }

  // Perform the actual computation
  detectKeypoints(output);

  deinitCompute ();

  // Reset the surface
  if (input_ == surface_)
    surface_.reset ();
}

---

pcl
Author(s): See http://pcl.ros.org/authors for the complete list of authors.
autogenerated on Fri Jan 11 09:55:22 2013