Point Cloud Library (PCL) 1.14.0
Loading...
Searching...
No Matches
3dsc.h
1/*
2 * Software License Agreement (BSD License)
3 *
4 * Point Cloud Library (PCL) - www.pointclouds.org
5 * Copyright (c) 2010-2011, Willow Garage, Inc.
6 * Copyright (c) 2012-, Open Perception, Inc.
7 *
8 * All rights reserved.
9 *
10 * Redistribution and use in source and binary forms, with or without
11 * modification, are permitted provided that the following conditions
12 * are met:
13 *
14 * * Redistributions of source code must retain the above copyright
15 * notice, this list of conditions and the following disclaimer.
16 * * Redistributions in binary form must reproduce the above
17 * copyright notice, this list of conditions and the following
18 * disclaimer in the documentation and/or other materials provided
19 * with the distribution.
20 * * Neither the name of the copyright holder(s) nor the names of its
21 * contributors may be used to endorse or promote products derived
22 * from this software without specific prior written permission.
23 *
24 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
25 * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
26 * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
27 * FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
28 * COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
29 * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
30 * BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
31 * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
32 * CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
33 * LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
34 * ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
35 * POSSIBILITY OF SUCH DAMAGE.
36 *
37 * $Id$
38 *
39 */
40
41#pragma once
42
43#include <random>
44
45#include <pcl/point_types.h>
46#include <pcl/features/feature.h>
47
48namespace pcl
49{
50 /** \brief ShapeContext3DEstimation implements the 3D shape context descriptor as
51 * described in:
52 * - Andrea Frome, Daniel Huber, Ravi Kolluri and Thomas Bülow, Jitendra Malik
53 * Recognizing Objects in Range Data Using Regional Point Descriptors,
54 * In proceedings of the 8th European Conference on Computer Vision (ECCV),
55 * Prague, May 11-14, 2004
56 *
57 * The suggested PointOutT is pcl::ShapeContext1980
58 *
59 * \attention
60 * The convention for a 3D shape context descriptor is:
61 * - if a query point's nearest neighbors cannot be estimated, the feature descriptor will be set to NaN (not a number), and the RF to 0
62 * - it is impossible to estimate a 3D shape context descriptor for a
63 * point that doesn't have finite 3D coordinates. Therefore, any point
64 * that contains NaN data on x, y, or z, will have its boundary feature
65 * property set to NaN.
66 *
67 * \author Alessandro Franchi, Samuele Salti, Federico Tombari (original code)
68 * \author Nizar Sallem (port to PCL)
69 * \ingroup features
70 */
71 template <typename PointInT, typename PointNT, typename PointOutT = pcl::ShapeContext1980>
72 class ShapeContext3DEstimation : public FeatureFromNormals<PointInT, PointNT, PointOutT>
73 {
74 public:
75 using Ptr = shared_ptr<ShapeContext3DEstimation<PointInT, PointNT, PointOutT> >;
76 using ConstPtr = shared_ptr<const ShapeContext3DEstimation<PointInT, PointNT, PointOutT> >;
77
78 using Feature<PointInT, PointOutT>::feature_name_;
79 using Feature<PointInT, PointOutT>::getClassName;
80 using Feature<PointInT, PointOutT>::indices_;
81 using Feature<PointInT, PointOutT>::search_parameter_;
82 using Feature<PointInT, PointOutT>::search_radius_;
83 using Feature<PointInT, PointOutT>::surface_;
84 using Feature<PointInT, PointOutT>::input_;
85 using Feature<PointInT, PointOutT>::searchForNeighbors;
86 using FeatureFromNormals<PointInT, PointNT, PointOutT>::normals_;
87
90
91 /** \brief Constructor.
92 * \param[in] random If true the random seed is set to current time, else it is
93 * set to 12345 prior to computing the descriptor (used to select X axis)
94 */
95 ShapeContext3DEstimation (bool random = false) :
99 volume_lut_(0),
100
101 rng_dist_ (0.0f, 1.0f)
102 {
103 feature_name_ = "ShapeContext3DEstimation";
104 search_radius_ = 2.5;
105
106 // Create a random number generator object
107 if (random)
108 {
109 std::random_device rd;
110 rng_.seed (rd());
111 }
112 else
113 rng_.seed (12345u);
114 }
115
116 ~ShapeContext3DEstimation() override = default;
117
118 //inline void
119 //setAzimuthBins (std::size_t bins) { azimuth_bins_ = bins; }
120
121 /** \return the number of bins along the azimuth */
122 inline std::size_t
124
125 //inline void
126 //setElevationBins (std::size_t bins) { elevation_bins_ = bins; }
127
128 /** \return The number of bins along the elevation */
129 inline std::size_t
131
132 //inline void
133 //setRadiusBins (std::size_t bins) { radius_bins_ = bins; }
134
135 /** \return The number of bins along the radii direction */
136 inline std::size_t
138
139 /** \brief The minimal radius value for the search sphere (rmin) in the original paper
140 * \param[in] radius the desired minimal radius
141 */
142 inline void
143 setMinimalRadius (double radius) { min_radius_ = radius; }
144
145 /** \return The minimal sphere radius */
146 inline double
148
149 /** \brief This radius is used to compute local point density
150 * density = number of points within this radius
151 * \param[in] radius value of the point density search radius
152 */
153 inline void
154 setPointDensityRadius (double radius) { point_density_radius_ = radius; }
155
156 /** \return The point density search radius */
157 inline double
159
160 protected:
161 /** \brief Initialize computation by allocating all the intervals and the volume lookup table. */
162 bool
163 initCompute () override;
164
165 /** \brief Estimate a descriptor for a given point.
166 * \param[in] index the index of the point to estimate a descriptor for
167 * \param[in] normals a pointer to the set of normals
168 * \param[out] rf the reference frame
169 * \param[out] desc the resultant estimated descriptor
170 * \return true if the descriptor was computed successfully, false if there was an error
171 * (e.g. the nearest neighbor didn't return any neighbors)
172 */
173 bool
174 computePoint (std::size_t index, const pcl::PointCloud<PointNT> &normals, float rf[9], std::vector<float> &desc);
175
176 /** \brief Estimate the actual feature.
177 * \param[out] output the resultant feature
178 */
179 void
180 computeFeature (PointCloudOut &output) override;
181
182 /** \brief Values of the radii interval */
183 std::vector<float> radii_interval_;
184
185 /** \brief Theta divisions interval */
186 std::vector<float> theta_divisions_;
187
188 /** \brief Phi divisions interval */
189 std::vector<float> phi_divisions_;
190
191 /** \brief Volumes look up table */
192 std::vector<float> volume_lut_;
193
194 /** \brief Bins along the azimuth dimension */
195 std::size_t azimuth_bins_{12};
196
197 /** \brief Bins along the elevation dimension */
198 std::size_t elevation_bins_{11};
199
200 /** \brief Bins along the radius dimension */
201 std::size_t radius_bins_{15};
202
203 /** \brief Minimal radius value */
204 double min_radius_{0.1};
205
206 /** \brief Point density radius */
208
209 /** \brief Descriptor length */
210 std::size_t descriptor_length_{};
211
212 /** \brief Random number generator algorithm. */
213 std::mt19937 rng_;
214
215 /** \brief Random number generator distribution. */
216 std::uniform_real_distribution<float> rng_dist_;
217
218 /* \brief Shift computed descriptor "L" times along the azimuthal direction
219 * \param[in] block_size the size of each azimuthal block
220 * \param[in] desc at input desc == original descriptor and on output it contains
221 * shifted descriptor resized descriptor_length_ * azimuth_bins_
222 */
223 //void
224 //shiftAlongAzimuth (std::size_t block_size, std::vector<float>& desc);
225
226 /** \brief Boost-based random number generator. */
227 inline float
229 {
230 return (rng_dist_ (rng_));
231 }
232 };
233}
234
235#ifdef PCL_NO_PRECOMPILE
236#include <pcl/features/impl/3dsc.hpp>
237#endif
PointCloudNConstPtr normals_
A pointer to the input dataset that contains the point normals of the XYZ dataset.
Definition feature.h:349
Feature represents the base feature class.
Definition feature.h:107
double search_parameter_
The actual search parameter (from either search_radius_ or k_).
Definition feature.h:234
const std::string & getClassName() const
Get a string representation of the name of this class.
Definition feature.h:244
int searchForNeighbors(std::size_t index, double parameter, pcl::Indices &indices, std::vector< float > &distances) const
Search for k-nearest neighbors using the spatial locator from setSearchmethod, and the given surface ...
Definition feature.h:268
double search_radius_
The nearest neighbors search radius for each point.
Definition feature.h:237
std::string feature_name_
The feature name.
Definition feature.h:220
PointCloudInConstPtr surface_
An input point cloud describing the surface that is to be used for nearest neighbors estimation.
Definition feature.h:228
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
ShapeContext3DEstimation implements the 3D shape context descriptor as described in:
Definition 3dsc.h:73
std::uniform_real_distribution< float > rng_dist_
Random number generator distribution.
Definition 3dsc.h:216
void setMinimalRadius(double radius)
The minimal radius value for the search sphere (rmin) in the original paper.
Definition 3dsc.h:143
bool computePoint(std::size_t index, const pcl::PointCloud< PointNT > &normals, float rf[9], std::vector< float > &desc)
Estimate a descriptor for a given point.
Definition 3dsc.hpp:133
std::size_t azimuth_bins_
Bins along the azimuth dimension.
Definition 3dsc.h:195
std::size_t getAzimuthBins()
Definition 3dsc.h:123
bool initCompute() override
Initialize computation by allocating all the intervals and the volume lookup table.
Definition 3dsc.hpp:53
shared_ptr< const ShapeContext3DEstimation< PointInT, PointNT, PointOutT > > ConstPtr
Definition 3dsc.h:76
std::size_t radius_bins_
Bins along the radius dimension.
Definition 3dsc.h:201
typename Feature< PointInT, PointOutT >::PointCloudIn PointCloudIn
Definition 3dsc.h:89
std::vector< float > radii_interval_
Values of the radii interval.
Definition 3dsc.h:183
std::size_t getElevationBins()
Definition 3dsc.h:130
float rnd()
Boost-based random number generator.
Definition 3dsc.h:228
std::mt19937 rng_
Random number generator algorithm.
Definition 3dsc.h:213
typename Feature< PointInT, PointOutT >::PointCloudOut PointCloudOut
Definition 3dsc.h:88
double min_radius_
Minimal radius value.
Definition 3dsc.h:204
void computeFeature(PointCloudOut &output) override
Estimate the actual feature.
Definition 3dsc.hpp:255
double point_density_radius_
Point density radius.
Definition 3dsc.h:207
std::vector< float > volume_lut_
Volumes look up table.
Definition 3dsc.h:192
std::size_t descriptor_length_
Descriptor length.
Definition 3dsc.h:210
std::vector< float > theta_divisions_
Theta divisions interval.
Definition 3dsc.h:186
~ShapeContext3DEstimation() override=default
ShapeContext3DEstimation(bool random=false)
Constructor.
Definition 3dsc.h:95
std::vector< float > phi_divisions_
Phi divisions interval.
Definition 3dsc.h:189
std::size_t getRadiusBins()
Definition 3dsc.h:137
std::size_t elevation_bins_
Bins along the elevation dimension.
Definition 3dsc.h:198
shared_ptr< ShapeContext3DEstimation< PointInT, PointNT, PointOutT > > Ptr
Definition 3dsc.h:75
void setPointDensityRadius(double radius)
This radius is used to compute local point density density = number of points within this radius.
Definition 3dsc.h:154
Defines all the PCL implemented PointT point type structures.