Point Cloud Library (PCL) 1.15.0
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segment_differences.h
1/*
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37
38#pragma once
39
40#include <pcl/pcl_base.h>
41#include <pcl/pcl_macros.h>
42#include <pcl/search/search.h> // for Search
43
44namespace pcl
45{
46 ////////////////////////////////////////////////////////////////////////////////////////////
47 /** \brief Obtain the difference between two aligned point clouds as another point cloud, given a distance threshold.
48 * \param src the input point cloud source
49 * \param threshold the distance threshold (tolerance) for point correspondences. (e.g., check if f a point p1 from
50 * src has a correspondence > threshold than a point p2 from tgt)
51 * \param tree the spatial locator (e.g., kd-tree) used for nearest neighbors searching built over the target cloud
52 * \param output the resultant output point cloud difference
53 * \ingroup segmentation
54 */
55 template <typename PointT>
57 const pcl::PointCloud<PointT> &src,
58 double threshold,
59 const typename pcl::search::Search<PointT>::Ptr &tree,
61
62 ////////////////////////////////////////////////////////////////////////////////////////////
63 ////////////////////////////////////////////////////////////////////////////////////////////
64 ////////////////////////////////////////////////////////////////////////////////////////////
65 /** \brief @b SegmentDifferences obtains the difference between two spatially
66 * aligned point clouds and returns the difference between them for a maximum
67 * given distance threshold.
68 * \author Radu Bogdan Rusu
69 * \ingroup segmentation
70 */
71 template <typename PointT>
72 class SegmentDifferences: public PCLBase<PointT>
73 {
75
76 public:
80
82 using KdTreePtr = typename KdTree::Ptr;
83
86
87 /** \brief Empty constructor. */
88 SegmentDifferences () = default;
89
90 /** \brief Provide a pointer to the target dataset against which we
91 * compare the input cloud given in setInputCloud
92 *
93 * \param cloud the target PointCloud dataset
94 */
95 inline void
96 setTargetCloud (const PointCloudConstPtr &cloud) { target_ = cloud; }
97
98 /** \brief Get a pointer to the input target point cloud dataset. */
99 inline PointCloudConstPtr const
100 getTargetCloud () { return (target_); }
101
102 /** \brief Provide a pointer to the search object.
103 * \param tree a pointer to the spatial search object.
104 */
105 inline void
106 setSearchMethod (const KdTreePtr &tree) { tree_ = tree; }
107
108 /** \brief Get a pointer to the search method used. */
109 inline KdTreePtr
110 getSearchMethod () { return (tree_); }
111
112 /** \brief Set the maximum distance tolerance (squared) between corresponding
113 * points in the two input datasets.
114 *
115 * \param sqr_threshold the squared distance tolerance as a measure in L2 Euclidean space
116 */
117 inline void
118 setDistanceThreshold (double sqr_threshold) { distance_threshold_ = sqr_threshold; }
119
120 /** \brief Get the squared distance tolerance between corresponding points as a
121 * measure in the L2 Euclidean space.
122 */
123 inline double
125
126 /** \brief Segment differences between two input point clouds.
127 * \param output the resultant difference between the two point clouds as a PointCloud
128 */
129 void
130 segment (PointCloud &output);
131
132 protected:
133 // Members derived from the base class
138
139 /** \brief A pointer to the spatial search object. */
140 KdTreePtr tree_{nullptr};
141
142 /** \brief The input target point cloud dataset. */
144
145 /** \brief The distance tolerance (squared) as a measure in the L2
146 * Euclidean space between corresponding points.
147 */
149
150 /** \brief Class getName method. */
151 virtual std::string
152 getClassName () const { return ("SegmentDifferences"); }
153 };
154}
155
156#ifdef PCL_NO_PRECOMPILE
157#include <pcl/segmentation/impl/segment_differences.hpp>
158#endif
PCL base class.
Definition pcl_base.h:70
PointCloudConstPtr input_
The input point cloud dataset.
Definition pcl_base.h:147
IndicesPtr indices_
A pointer to the vector of point indices to use.
Definition pcl_base.h:150
bool initCompute()
This method should get called before starting the actual computation.
Definition pcl_base.hpp:138
bool deinitCompute()
This method should get called after finishing the actual computation.
Definition pcl_base.hpp:175
PointCloud represents the base class in PCL for storing collections of 3D points.
shared_ptr< PointCloud< PointT > > Ptr
shared_ptr< const PointCloud< PointT > > ConstPtr
SegmentDifferences obtains the difference between two spatially aligned point clouds and returns the ...
void setSearchMethod(const KdTreePtr &tree)
Provide a pointer to the search object.
void setTargetCloud(const PointCloudConstPtr &cloud)
Provide a pointer to the target dataset against which we compare the input cloud given in setInputClo...
double getDistanceThreshold()
Get the squared distance tolerance between corresponding points as a measure in the L2 Euclidean spac...
PointIndices::ConstPtr PointIndicesConstPtr
void segment(PointCloud &output)
Segment differences between two input point clouds.
KdTreePtr tree_
A pointer to the spatial search object.
PointCloudConstPtr target_
The input target point cloud dataset.
PointCloudConstPtr const getTargetCloud()
Get a pointer to the input target point cloud dataset.
KdTreePtr getSearchMethod()
Get a pointer to the search method used.
typename PointCloud::Ptr PointCloudPtr
typename KdTree::Ptr KdTreePtr
void setDistanceThreshold(double sqr_threshold)
Set the maximum distance tolerance (squared) between corresponding points in the two input datasets.
PointIndices::Ptr PointIndicesPtr
typename PointCloud::ConstPtr PointCloudConstPtr
double distance_threshold_
The distance tolerance (squared) as a measure in the L2 Euclidean space between corresponding points.
virtual std::string getClassName() const
Class getName method.
SegmentDifferences()=default
Empty constructor.
Generic search class.
Definition search.h:75
shared_ptr< pcl::search::Search< PointT > > Ptr
Definition search.h:81
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...
Defines all the PCL and non-PCL macros used.
shared_ptr< ::pcl::PointIndices > Ptr
shared_ptr< const ::pcl::PointIndices > ConstPtr