Point Cloud Library (PCL) 1.13.0
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greedy_verification.hpp
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36
37#pragma once
38#include <pcl/recognition/hv/greedy_verification.h>
39
40template<typename ModelT, typename SceneT>
41 void
43 {
44 //clear stuff
45 recognition_models_.clear ();
46 points_explained_by_rm_.clear ();
47
48 // initialize mask...
49 mask_.resize (visible_models_.size ());
50 for (std::size_t i = 0; i < visible_models_.size (); i++)
51 mask_[i] = false;
52
53 // initialize explained_by_RM
54 points_explained_by_rm_.resize (scene_cloud_downsampled_->size ());
55
56 // initialize model
57 for (std::size_t m = 0; m < visible_models_.size (); m++)
58 {
59 RecognitionModelPtr recog_model (new RecognitionModel);
60 // voxelize model cloud
61 recog_model->cloud_.reset (new pcl::PointCloud<ModelT>);
62 recog_model->id_ = static_cast<int> (m);
63
64 pcl::VoxelGrid<ModelT> voxel_grid;
65 voxel_grid.setInputCloud (visible_models_[m]);
66 voxel_grid.setLeafSize (resolution_, resolution_, resolution_);
67 voxel_grid.filter (*(recog_model->cloud_));
68
69 std::vector<int> explained_indices;
70 std::vector<int> outliers;
71 pcl::Indices nn_indices;
72 std::vector<float> nn_distances;
73
74 for (std::size_t i = 0; i < recog_model->cloud_->size (); i++)
75 {
76 if (!scene_downsampled_tree_->radiusSearch ((*recog_model->cloud_)[i], inliers_threshold_, nn_indices, nn_distances,
77 std::numeric_limits<int>::max ()))
78 {
79 outliers.push_back (static_cast<int> (i));
80 }
81 else
82 {
83 for (std::size_t k = 0; k < nn_distances.size (); k++)
84 {
85 explained_indices.push_back (nn_indices[k]); //nn_indices[k] points to the scene
86 }
87 }
88 }
89
90 std::sort (explained_indices.begin (), explained_indices.end ());
91 explained_indices.erase (std::unique (explained_indices.begin (), explained_indices.end ()), explained_indices.end ());
92
93 recog_model->bad_information_ = static_cast<int> (outliers.size ());
94 recog_model->explained_ = explained_indices;
95 recog_model->good_information_ = static_cast<int> (explained_indices.size ());
96 recog_model->regularizer_ = regularizer_;
97
98 recognition_models_.push_back (recog_model);
99
100 for (const int &explained_index : explained_indices)
101 {
102 points_explained_by_rm_[explained_index].push_back (recog_model);
103 }
104 }
105
106 sortModels ();
107 }
108
109template<typename ModelT, typename SceneT>
110 void
112 {
113 initialize ();
114
115 std::vector<bool> best_solution_;
116 best_solution_.resize (recognition_models_.size ());
117
118 for (std::size_t i = 0; i < recognition_models_.size (); i++)
119 {
120 if (static_cast<float> (recognition_models_[i]->good_information_) > (regularizer_
121 * static_cast<float> (recognition_models_[i]->bad_information_)))
122 {
123 best_solution_[i] = true;
124 updateGoodInformation (static_cast<int> (i));
125 }
126 else
127 best_solution_[i] = false;
128 }
129
130 for (std::size_t i = 0; i < best_solution_.size (); i++)
131 {
132 if (best_solution_[i])
133 {
134 mask_[indices_models_[i].index_] = true;
135 }
136 else
137 {
138 mask_[indices_models_[i].index_] = false;
139 }
140 }
141 }
142
143#define PCL_INSTANTIATE_GreedyVerification(T1,T2) template class PCL_EXPORTS pcl::GreedyVerification<T1,T2>;
void filter(PointCloud &output)
Calls the filtering method and returns the filtered dataset in output.
Definition filter.h:121
A greedy hypothesis verification method.
void verify() override
Starts verification.
virtual void setInputCloud(const PointCloudConstPtr &cloud)
Provide a pointer to the input dataset.
Definition pcl_base.hpp:65
PointCloud represents the base class in PCL for storing collections of 3D points.
VoxelGrid assembles a local 3D grid over a given PointCloud, and downsamples + filters the data.
Definition voxel_grid.h:177
void setLeafSize(const Eigen::Vector4f &leaf_size)
Set the voxel grid leaf size.
Definition voxel_grid.h:221
IndicesAllocator<> Indices
Type used for indices in PCL.
Definition types.h:133