Point Cloud Library (PCL) 1.13.1
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segment_differences.hpp
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37
38#pragma once
39
40#include <pcl/segmentation/segment_differences.h>
41
42#include <pcl/common/io.h>
43#include <pcl/common/point_tests.h> // for pcl::isFinite
44#include <pcl/search/organized.h> // for OrganizedNeighbor
45#include <pcl/search/kdtree.h> // for KdTree
46
47
48//////////////////////////////////////////////////////////////////////////
49template <typename PointT> void
51 const pcl::PointCloud<PointT> &src,
52 double threshold,
53 const typename pcl::search::Search<PointT>::Ptr &tree,
55{
56 // We're interested in a single nearest neighbor only
57 Indices nn_indices (1);
58 std::vector<float> nn_distances (1);
59
60 // The input cloud indices that do not have a neighbor in the target cloud
61 Indices src_indices;
62
63 // Iterate through the source data set
64 for (index_t i = 0; i < static_cast<index_t> (src.size ()); ++i)
65 {
66 // Ignore invalid points in the input cloud
67 if (!isFinite (src[i]))
68 continue;
69 // Search for the closest point in the target data set (number of neighbors to find = 1)
70 if (!tree->nearestKSearch (src[i], 1, nn_indices, nn_distances))
71 {
72 PCL_WARN ("No neighbor found for point %lu (%f %f %f)!\n", i, src[i].x, src[i].y, src[i].z);
73 continue;
74 }
75 // Add points without a corresponding point in the target cloud to the output cloud
76 if (nn_distances[0] > threshold)
77 src_indices.push_back (i);
78 }
79
80 // Copy all the data fields from the input cloud to the output one
81 copyPointCloud (src, src_indices, output);
82
83 // Output is always dense, as invalid points in the input cloud are ignored
84 output.is_dense = true;
85}
86
87//////////////////////////////////////////////////////////////////////////
88//////////////////////////////////////////////////////////////////////////
89//////////////////////////////////////////////////////////////////////////
90template <typename PointT> void
92{
93 output.header = input_->header;
94
95 if (!initCompute ())
96 {
97 output.width = output.height = 0;
98 output.clear ();
99 return;
100 }
101
102 // If target is empty, input - target = input
103 if (target_->points.empty ())
104 {
105 output = *input_;
106 return;
107 }
108
109 // Initialize the spatial locator
110 if (!tree_)
111 {
112 if (target_->isOrganized ())
113 tree_.reset (new pcl::search::OrganizedNeighbor<PointT> ());
114 else
115 tree_.reset (new pcl::search::KdTree<PointT> (false));
116 }
117 // Send the input dataset to the spatial locator
118 tree_->setInputCloud (target_);
119
120 getPointCloudDifference (*input_, distance_threshold_, tree_, output);
121
122 deinitCompute ();
123}
124
125#define PCL_INSTANTIATE_SegmentDifferences(T) template class PCL_EXPORTS pcl::SegmentDifferences<T>;
126#define PCL_INSTANTIATE_getPointCloudDifference(T) template PCL_EXPORTS void pcl::getPointCloudDifference<T>(const pcl::PointCloud<T> &, double, const typename pcl::search::Search<T>::Ptr &, pcl::PointCloud<T> &);
127
PointCloud represents the base class in PCL for storing collections of 3D points.
bool is_dense
True if no points are invalid (e.g., have NaN or Inf values in any of their floating point fields).
std::uint32_t width
The point cloud width (if organized as an image-structure).
pcl::PCLHeader header
The point cloud header.
std::uint32_t height
The point cloud height (if organized as an image-structure).
void clear()
Removes all points in a cloud and sets the width and height to 0.
std::size_t size() const
void segment(PointCloud &output)
Segment differences between two input point clouds.
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 neighbor search in organized point clouds.
Definition organized.h:61
shared_ptr< pcl::search::Search< PointT > > Ptr
Definition search.h:81
virtual int nearestKSearch(const PointT &point, int k, Indices &k_indices, std::vector< float > &k_sqr_distances) const =0
Search for the k-nearest neighbors for the given query point.
void copyPointCloud(const pcl::PointCloud< PointInT > &cloud_in, pcl::PointCloud< PointOutT > &cloud_out)
Copy all the fields from a given point cloud into a new point cloud.
Definition io.hpp:142
void getPointCloudDifference(const pcl::PointCloud< PointT > &src, double threshold, const typename pcl::search::Search< PointT >::Ptr &tree, pcl::PointCloud< PointT > &output)
Obtain the difference between two aligned point clouds as another point cloud, given a distance thres...
bool isFinite(const PointT &pt)
Tests if the 3D components of a point are all finite param[in] pt point to be tested return true if f...
Definition point_tests.h:55
detail::int_type_t< detail::index_type_size, detail::index_type_signed > index_t
Type used for an index in PCL.
Definition types.h:112
IndicesAllocator<> Indices
Type used for indices in PCL.
Definition types.h:133