Point Cloud Library (PCL) 1.12.0
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convolution_3d.hpp
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39
40#ifndef PCL_FILTERS_CONVOLUTION_3D_IMPL_HPP
41#define PCL_FILTERS_CONVOLUTION_3D_IMPL_HPP
42
43#include <pcl/pcl_config.h>
44#include <pcl/point_types.h>
45
46#include <cmath>
47#include <cstdint>
48#include <limits>
49#include <vector>
50
51///////////////////////////////////////////////////////////////////////////////////////////////////
52namespace pcl
53{
54 namespace filters
55 {
56 template <typename PointT>
58 {
59 void
61 {
62 n.normal_x = n.normal_y = n.normal_z = std::numeric_limits<float>::quiet_NaN ();
63 }
64 };
65
66 template <typename PointT> class
68 {
69 void
70 makeInfinite (pcl::PointXY& p)
71 {
72 p.x = p.y = std::numeric_limits<float>::quiet_NaN ();
73 }
74 };
75 }
76}
77
78///////////////////////////////////////////////////////////////////////////////////////////////////
79template<typename PointInT, typename PointOutT> bool
81{
82 if (sigma_ == 0)
83 {
84 PCL_ERROR ("Sigma is not set or equal to 0!\n", sigma_);
85 return (false);
86 }
87 sigma_sqr_ = sigma_ * sigma_;
88
89 if (sigma_coefficient_)
90 {
91 if ((*sigma_coefficient_) > 6 || (*sigma_coefficient_) < 3)
92 {
93 PCL_ERROR ("Sigma coefficient (%f) out of [3..6]!\n", (*sigma_coefficient_));
94 return (false);
95 }
96 else
97 threshold_ = (*sigma_coefficient_) * (*sigma_coefficient_) * sigma_sqr_;
98 }
99
100 return (true);
101}
102
103///////////////////////////////////////////////////////////////////////////////////////////////////
104template<typename PointInT, typename PointOutT> PointOutT
106 const std::vector<float>& distances)
107{
108 using namespace pcl::common;
109 PointOutT result;
110 float total_weight = 0;
111 std::vector<float>::const_iterator dist_it = distances.begin ();
112
113 for (Indices::const_iterator idx_it = indices.begin ();
114 idx_it != indices.end ();
115 ++idx_it, ++dist_it)
116 {
117 if (*dist_it <= threshold_ && isFinite ((*input_) [*idx_it]))
118 {
119 float weight = std::exp (-0.5f * (*dist_it) / sigma_sqr_);
120 result += weight * (*input_) [*idx_it];
121 total_weight += weight;
122 }
123 }
124 if (total_weight != 0)
125 result /= total_weight;
126 else
127 makeInfinite (result);
128
129 return (result);
130}
131
132///////////////////////////////////////////////////////////////////////////////////////////////////////
133template<typename PointInT, typename PointOutT> PointOutT
134pcl::filters::GaussianKernelRGB<PointInT, PointOutT>::operator() (const Indices& indices, const std::vector<float>& distances)
135{
136 using namespace pcl::common;
137 PointOutT result;
138 float total_weight = 0;
139 float r = 0, g = 0, b = 0;
140 std::vector<float>::const_iterator dist_it = distances.begin ();
141
142 for (Indices::const_iterator idx_it = indices.begin ();
143 idx_it != indices.end ();
144 ++idx_it, ++dist_it)
145 {
146 if (*dist_it <= threshold_ && isFinite ((*input_) [*idx_it]))
147 {
148 float weight = std::exp (-0.5f * (*dist_it) / sigma_sqr_);
149 result.x += weight * (*input_) [*idx_it].x;
150 result.y += weight * (*input_) [*idx_it].y;
151 result.z += weight * (*input_) [*idx_it].z;
152 r += weight * static_cast<float> ((*input_) [*idx_it].r);
153 g += weight * static_cast<float> ((*input_) [*idx_it].g);
154 b += weight * static_cast<float> ((*input_) [*idx_it].b);
155 total_weight += weight;
156 }
157 }
158 if (total_weight != 0)
159 {
160 total_weight = 1.f/total_weight;
161 r*= total_weight; g*= total_weight; b*= total_weight;
162 result.x*= total_weight; result.y*= total_weight; result.z*= total_weight;
163 result.r = static_cast<std::uint8_t> (r);
164 result.g = static_cast<std::uint8_t> (g);
165 result.b = static_cast<std::uint8_t> (b);
166 }
167 else
168 makeInfinite (result);
169
170 return (result);
171}
172
173///////////////////////////////////////////////////////////////////////////////////////////////////
174template <typename PointInT, typename PointOutT, typename KernelT>
176 : PCLBase <PointInT> ()
177 , surface_ ()
178 , tree_ ()
179 , search_radius_ (0)
180{}
181
182///////////////////////////////////////////////////////////////////////////////////////////////////
183template <typename PointInT, typename PointOutT, typename KernelT> bool
185{
187 {
188 PCL_ERROR ("[pcl::filters::Convlution3D::initCompute] init failed!\n");
189 return (false);
190 }
191 // Initialize the spatial locator
192 if (!tree_)
193 {
194 if (input_->isOrganized ())
195 tree_.reset (new pcl::search::OrganizedNeighbor<PointInT> ());
196 else
197 tree_.reset (new pcl::search::KdTree<PointInT> (false));
198 }
199 // If no search surface has been defined, use the input dataset as the search surface itself
200 if (!surface_)
201 surface_ = input_;
202 // Send the surface dataset to the spatial locator
203 tree_->setInputCloud (surface_);
204 // Do a fast check to see if the search parameters are well defined
205 if (search_radius_ <= 0.0)
206 {
207 PCL_ERROR ("[pcl::filters::Convlution3D::initCompute] search radius (%f) must be > 0\n",
208 search_radius_);
209 return (false);
210 }
211 // Make sure the provided kernel implements the required interface
212 if (dynamic_cast<ConvolvingKernel<PointInT, PointOutT>* > (&kernel_) == 0)
213 {
214 PCL_ERROR ("[pcl::filters::Convlution3D::initCompute] init failed : ");
215 PCL_ERROR ("kernel_ must implement ConvolvingKernel interface\n!");
216 return (false);
217 }
218 kernel_.setInputCloud (surface_);
219 // Initialize convolving kernel
220 if (!kernel_.initCompute ())
221 {
222 PCL_ERROR ("[pcl::filters::Convlution3D::initCompute] kernel initialization failed!\n");
223 return (false);
224 }
225 return (true);
226}
227
228///////////////////////////////////////////////////////////////////////////////////////////////////
229template <typename PointInT, typename PointOutT, typename KernelT> void
231{
232 if (!initCompute ())
233 {
234 PCL_ERROR ("[pcl::filters::Convlution3D::convolve] init failed!\n");
235 return;
236 }
237 output.resize (surface_->size ());
238 output.width = surface_->width;
239 output.height = surface_->height;
240 output.is_dense = surface_->is_dense;
241 Indices nn_indices;
242 std::vector<float> nn_distances;
243
244#pragma omp parallel for \
245 default(none) \
246 shared(output) \
247 firstprivate(nn_indices, nn_distances) \
248 num_threads(threads_)
249 for (std::int64_t point_idx = 0; point_idx < static_cast<std::int64_t> (surface_->size ()); ++point_idx)
250 {
251 const PointInT& point_in = surface_->points [point_idx];
252 PointOutT& point_out = output [point_idx];
253 if (isFinite (point_in) &&
254 tree_->radiusSearch (point_in, search_radius_, nn_indices, nn_distances))
255 {
256 point_out = kernel_ (nn_indices, nn_distances);
257 }
258 else
259 {
260 kernel_.makeInfinite (point_out);
261 output.is_dense = false;
262 }
263 }
264}
265
266#endif
PCL base class.
Definition pcl_base.h:70
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).
void resize(std::size_t count)
Resizes the container to contain count elements.
std::uint32_t width
The point cloud width (if organized as an image-structure).
std::uint32_t height
The point cloud height (if organized as an image-structure).
bool initCompute()
initialize computation
void convolve(PointCloudOut &output)
Convolve point cloud.
Class ConvolvingKernel base class for all convolving kernels.
static void makeInfinite(PointOutT &p)
Utility function that annihilates a point making it fail the pcl::isFinite test.
virtual PointOutT operator()(const Indices &indices, const std::vector< float > &distances)
Convolve point at the center of this local information.
bool initCompute()
Must call this method before doing any computation.
PointOutT operator()(const Indices &indices, const std::vector< float > &distances)
Convolve point at the center of this local information.
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
Defines all the PCL implemented PointT point type structures.
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
IndicesAllocator<> Indices
Type used for indices in PCL.
Definition types.h:133
A point structure representing normal coordinates and the surface curvature estimate.
A 2D point structure representing Euclidean xy coordinates.
A point structure representing Euclidean xyz coordinates, and the RGB color.