Point Cloud Library (PCL)  1.12.1-dev
radius_outlier_removal.hpp
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39 
40 #ifndef PCL_FILTERS_IMPL_RADIUS_OUTLIER_REMOVAL_H_
41 #define PCL_FILTERS_IMPL_RADIUS_OUTLIER_REMOVAL_H_
42 
43 #include <pcl/filters/radius_outlier_removal.h>
44 #include <pcl/search/organized.h> // for OrganizedNeighbor
45 #include <pcl/search/kdtree.h> // for KdTree
46 
47 ////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
48 template <typename PointT> void
50 {
51  if (search_radius_ == 0.0)
52  {
53  PCL_ERROR ("[pcl::%s::applyFilter] No radius defined!\n", getClassName ().c_str ());
54  indices.clear ();
55  removed_indices_->clear ();
56  return;
57  }
58 
59  // Initialize the search class
60  if (!searcher_)
61  {
62  if (input_->isOrganized ())
63  searcher_.reset (new pcl::search::OrganizedNeighbor<PointT> ());
64  else
65  searcher_.reset (new pcl::search::KdTree<PointT> (false));
66  }
67  searcher_->setInputCloud (input_);
68 
69  // The arrays to be used
70  Indices nn_indices (indices_->size ());
71  std::vector<float> nn_dists (indices_->size ());
72  indices.resize (indices_->size ());
73  removed_indices_->resize (indices_->size ());
74  int oii = 0, rii = 0; // oii = output indices iterator, rii = removed indices iterator
75 
76  // If the data is dense => use nearest-k search
77  if (input_->is_dense)
78  {
79  // Note: k includes the query point, so is always at least 1
80  int mean_k = min_pts_radius_ + 1;
81  double nn_dists_max = search_radius_ * search_radius_;
82 
83  for (const auto& index : (*indices_))
84  {
85  // Perform the nearest-k search
86  int k = searcher_->nearestKSearch (index, mean_k, nn_indices, nn_dists);
87 
88  // Check the number of neighbors
89  // Note: nn_dists is sorted, so check the last item
90  bool chk_neighbors = true;
91  if (k == mean_k)
92  {
93  if (negative_)
94  {
95  chk_neighbors = false;
96  if (nn_dists_max < nn_dists[k-1])
97  {
98  chk_neighbors = true;
99  }
100  }
101  else
102  {
103  chk_neighbors = true;
104  if (nn_dists_max < nn_dists[k-1])
105  {
106  chk_neighbors = false;
107  }
108  }
109  }
110  else
111  {
112  if (negative_)
113  chk_neighbors = true;
114  else
115  chk_neighbors = false;
116  }
117 
118  // Points having too few neighbors are outliers and are passed to removed indices
119  // Unless negative was set, then it's the opposite condition
120  if (!chk_neighbors)
121  {
122  if (extract_removed_indices_)
123  (*removed_indices_)[rii++] = index;
124  continue;
125  }
126 
127  // Otherwise it was a normal point for output (inlier)
128  indices[oii++] = index;
129  }
130  }
131  // NaN or Inf values could exist => use radius search
132  else
133  {
134  for (const auto& index : (*indices_))
135  {
136  // Perform the radius search
137  // Note: k includes the query point, so is always at least 1
138  int k = searcher_->radiusSearch (index, search_radius_, nn_indices, nn_dists);
139 
140  // Points having too few neighbors are outliers and are passed to removed indices
141  // Unless negative was set, then it's the opposite condition
142  if ((!negative_ && k <= min_pts_radius_) || (negative_ && k > min_pts_radius_))
143  {
144  if (extract_removed_indices_)
145  (*removed_indices_)[rii++] = index;
146  continue;
147  }
148 
149  // Otherwise it was a normal point for output (inlier)
150  indices[oii++] = index;
151  }
152  }
153 
154  // Resize the output arrays
155  indices.resize (oii);
156  removed_indices_->resize (rii);
157 }
158 
159 #define PCL_INSTANTIATE_RadiusOutlierRemoval(T) template class PCL_EXPORTS pcl::RadiusOutlierRemoval<T>;
160 
161 #endif // PCL_FILTERS_IMPL_RADIUS_OUTLIER_REMOVAL_H_
162 
void applyFilterIndices(Indices &indices)
Filtered results are indexed by an indices array.
search::KdTree is a wrapper class which inherits the pcl::KdTree class for performing search function...
Definition: kdtree.h:62
OrganizedNeighbor is a class for optimized nearest neigbhor search in organized point clouds.
Definition: organized.h:61
IndicesAllocator<> Indices
Type used for indices in PCL.
Definition: types.h:133