Point Cloud Library (PCL) 1.12.1
statistical_outlier_removal.hpp
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39
40#ifndef PCL_FILTERS_IMPL_STATISTICAL_OUTLIER_REMOVAL_H_
41#define PCL_FILTERS_IMPL_STATISTICAL_OUTLIER_REMOVAL_H_
42
43#include <pcl/filters/statistical_outlier_removal.h>
44#include <pcl/search/organized.h> // for OrganizedNeighbor
45#include <pcl/search/kdtree.h> // for KdTree
46
47////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
48template <typename PointT> void
50{
51 // Initialize the search class
52 if (!searcher_)
53 {
54 if (input_->isOrganized ())
55 searcher_.reset (new pcl::search::OrganizedNeighbor<PointT> ());
56 else
57 searcher_.reset (new pcl::search::KdTree<PointT> (false));
58 }
59 searcher_->setInputCloud (input_);
60
61 // The arrays to be used
62 Indices nn_indices (mean_k_);
63 std::vector<float> nn_dists (mean_k_);
64 std::vector<float> distances (indices_->size ());
65 indices.resize (indices_->size ());
66 removed_indices_->resize (indices_->size ());
67 int oii = 0, rii = 0; // oii = output indices iterator, rii = removed indices iterator
68
69 // First pass: Compute the mean distances for all points with respect to their k nearest neighbors
70 int valid_distances = 0;
71 for (int iii = 0; iii < static_cast<int> (indices_->size ()); ++iii) // iii = input indices iterator
72 {
73 if (!std::isfinite ((*input_)[(*indices_)[iii]].x) ||
74 !std::isfinite ((*input_)[(*indices_)[iii]].y) ||
75 !std::isfinite ((*input_)[(*indices_)[iii]].z))
76 {
77 distances[iii] = 0.0;
78 continue;
79 }
80
81 // Perform the nearest k search
82 if (searcher_->nearestKSearch ((*indices_)[iii], mean_k_ + 1, nn_indices, nn_dists) == 0)
83 {
84 distances[iii] = 0.0;
85 PCL_WARN ("[pcl::%s::applyFilter] Searching for the closest %d neighbors failed.\n", getClassName ().c_str (), mean_k_);
86 continue;
87 }
88
89 // Calculate the mean distance to its neighbors
90 double dist_sum = 0.0;
91 for (int k = 1; k < mean_k_ + 1; ++k) // k = 0 is the query point
92 dist_sum += sqrt (nn_dists[k]);
93 distances[iii] = static_cast<float> (dist_sum / mean_k_);
94 valid_distances++;
95 }
96
97 // Estimate the mean and the standard deviation of the distance vector
98 double sum = 0, sq_sum = 0;
99 for (const float &distance : distances)
100 {
101 sum += distance;
102 sq_sum += distance * distance;
103 }
104 double mean = sum / static_cast<double>(valid_distances);
105 double variance = (sq_sum - sum * sum / static_cast<double>(valid_distances)) / (static_cast<double>(valid_distances) - 1);
106 double stddev = sqrt (variance);
107 //getMeanStd (distances, mean, stddev);
108
109 double distance_threshold = mean + std_mul_ * stddev;
110
111 // Second pass: Classify the points on the computed distance threshold
112 for (int iii = 0; iii < static_cast<int> (indices_->size ()); ++iii) // iii = input indices iterator
113 {
114 // Points having a too high average distance are outliers and are passed to removed indices
115 // Unless negative was set, then it's the opposite condition
116 if ((!negative_ && distances[iii] > distance_threshold) || (negative_ && distances[iii] <= distance_threshold))
117 {
118 if (extract_removed_indices_)
119 (*removed_indices_)[rii++] = (*indices_)[iii];
120 continue;
121 }
122
123 // Otherwise it was a normal point for output (inlier)
124 indices[oii++] = (*indices_)[iii];
125 }
126
127 // Resize the output arrays
128 indices.resize (oii);
129 removed_indices_->resize (rii);
130}
131
132#define PCL_INSTANTIATE_StatisticalOutlierRemoval(T) template class PCL_EXPORTS pcl::StatisticalOutlierRemoval<T>;
133
134#endif // PCL_FILTERS_IMPL_STATISTICAL_OUTLIER_REMOVAL_H_
135
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
float distance(const PointT &p1, const PointT &p2)
Definition: geometry.h:60
IndicesAllocator<> Indices
Type used for indices in PCL.
Definition: types.h:133