Point Cloud Library (PCL) 1.12.0
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correspondence_rejection_sample_consensus.h
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40
41#pragma once
42
43#include <pcl/registration/correspondence_rejection.h>
44#include <pcl/memory.h>
45
46namespace pcl {
47namespace registration {
48/** \brief CorrespondenceRejectorSampleConsensus implements a correspondence rejection
49 * using Random Sample Consensus to identify inliers (and reject outliers)
50 * \author Dirk Holz
51 * \ingroup registration
52 */
53template <typename PointT>
56 using PointCloudPtr = typename PointCloud::Ptr;
57 using PointCloudConstPtr = typename PointCloud::ConstPtr;
58
59public:
63
64 using Ptr = shared_ptr<CorrespondenceRejectorSampleConsensus<PointT>>;
65 using ConstPtr = shared_ptr<const CorrespondenceRejectorSampleConsensus<PointT>>;
66
67 /** \brief Empty constructor. Sets the inlier threshold to 5cm (0.05m),
68 * and the maximum number of iterations to 1000.
69 */
71 : inlier_threshold_(0.05)
72 , max_iterations_(1000) // std::numeric_limits<int>::max ()
73 , input_()
75 , target_()
76 , refine_(false)
77 , save_inliers_(false)
78 {
79 rejection_name_ = "CorrespondenceRejectorSampleConsensus";
80 }
81
82 /** \brief Empty destructor. */
84
85 /** \brief Get a list of valid correspondences after rejection from the original set
86 * of correspondences. \param[in] original_correspondences the set of initial
87 * correspondences given \param[out] remaining_correspondences the resultant filtered
88 * set of remaining correspondences
89 */
90 inline void
91 getRemainingCorrespondences(const pcl::Correspondences& original_correspondences,
92 pcl::Correspondences& remaining_correspondences) override;
93
94 /** \brief Provide a source point cloud dataset (must contain XYZ data!)
95 * \param[in] cloud a cloud containing XYZ data
96 */
97 virtual inline void
98 setInputSource(const PointCloudConstPtr& cloud)
99 {
100 input_ = cloud;
101 }
102
103 /** \brief Get a pointer to the input point cloud dataset target. */
104 inline PointCloudConstPtr const
106 {
107 return (input_);
108 }
109
110 /** \brief Provide a target point cloud dataset (must contain XYZ data!)
111 * \param[in] cloud a cloud containing XYZ data
112 */
113 virtual inline void
114 setInputTarget(const PointCloudConstPtr& cloud)
115 {
116 target_ = cloud;
117 }
118
119 /** \brief Get a pointer to the input point cloud dataset target. */
120 inline PointCloudConstPtr const
122 {
123 return (target_);
124 }
125
126 /** \brief See if this rejector requires source points */
127 bool
128 requiresSourcePoints() const override
129 {
130 return (true);
131 }
132
133 /** \brief Blob method for setting the source cloud */
134 void
136 {
137 PointCloudPtr cloud(new PointCloud);
138 fromPCLPointCloud2(*cloud2, *cloud);
139 setInputSource(cloud);
140 }
141
142 /** \brief See if this rejector requires a target cloud */
143 bool
144 requiresTargetPoints() const override
145 {
146 return (true);
147 }
148
149 /** \brief Method for setting the target cloud */
150 void
152 {
153 PointCloudPtr cloud(new PointCloud);
154 fromPCLPointCloud2(*cloud2, *cloud);
155 setInputTarget(cloud);
156 }
157
158 /** \brief Set the maximum distance between corresponding points.
159 * Correspondences with distances below the threshold are considered as inliers.
160 * \param[in] threshold Distance threshold in the same dimension as source and target
161 * data sets.
162 */
163 inline void
164 setInlierThreshold(double threshold)
165 {
166 inlier_threshold_ = threshold;
167 };
168
169 /** \brief Get the maximum distance between corresponding points.
170 * \return Distance threshold in the same dimension as source and target data sets.
171 */
172 inline double
174 {
175 return inlier_threshold_;
176 };
177
178 /** \brief Set the maximum number of iterations.
179 * \param[in] max_iterations Maximum number if iterations to run
180 */
181 inline void
182 setMaximumIterations(int max_iterations)
183 {
184 max_iterations_ = std::max(max_iterations, 0);
185 }
186
187 /** \brief Get the maximum number of iterations.
188 * \return max_iterations Maximum number if iterations to run
189 */
190 inline int
192 {
193 return (max_iterations_);
194 }
195
196 /** \brief Get the best transformation after RANSAC rejection.
197 * \return The homogeneous 4x4 transformation yielding the largest number of inliers.
198 */
199 inline Eigen::Matrix4f
201 {
203 };
204
205 /** \brief Specify whether the model should be refined internally using the variance
206 * of the inliers \param[in] refine true if the model should be refined, false
207 * otherwise
208 */
209 inline void
210 setRefineModel(const bool refine)
211 {
212 refine_ = refine;
213 }
214
215 /** \brief Get the internal refine parameter value as set by the user using
216 * setRefineModel */
217 inline bool
219 {
220 return (refine_);
221 }
222
223 /** \brief Get the inlier indices found by the correspondence rejector. This
224 * information is only saved if setSaveInliers(true) was called in advance.
225 * \param[out] inlier_indices Indices for the inliers
226 */
227 inline void
229 {
230 inlier_indices = inlier_indices_;
231 }
232
233 /** \brief Set whether to save inliers or not
234 * \param[in] s True to save inliers / False otherwise
235 */
236 inline void
238 {
239 save_inliers_ = s;
240 }
241
242 /** \brief Get whether the rejector is configured to save inliers */
243 inline bool
245 {
246 return save_inliers_;
247 }
248
249protected:
250 /** \brief Apply the rejection algorithm.
251 * \param[out] correspondences the set of resultant correspondences.
252 */
253 inline void
254 applyRejection(pcl::Correspondences& correspondences) override
255 {
257 }
258
260
262
263 PointCloudConstPtr input_;
264 PointCloudPtr input_transformed_;
265 PointCloudConstPtr target_;
266
267 Eigen::Matrix4f best_transformation_;
268
272
273public:
275};
276} // namespace registration
277} // namespace pcl
278
279#include <pcl/registration/impl/correspondence_rejection_sample_consensus.hpp>
shared_ptr< const PointCloud< PointT > > ConstPtr
shared_ptr< PointCloud< PointT > > Ptr
CorrespondenceRejector represents the base class for correspondence rejection methods
CorrespondencesConstPtr input_correspondences_
The input correspondences.
std::string rejection_name_
The name of the rejection method.
const std::string & getClassName() const
Get a string representation of the name of this class.
CorrespondenceRejectorSampleConsensus implements a correspondence rejection using Random Sample Conse...
bool requiresSourcePoints() const override
See if this rejector requires source points.
double getInlierThreshold()
Get the maximum distance between corresponding points.
virtual void setInputSource(const PointCloudConstPtr &cloud)
Provide a source point cloud dataset (must contain XYZ data!)
shared_ptr< const CorrespondenceRejectorSampleConsensus< PointT > > ConstPtr
Eigen::Matrix4f getBestTransformation()
Get the best transformation after RANSAC rejection.
bool getSaveInliers()
Get whether the rejector is configured to save inliers.
virtual void setInputTarget(const PointCloudConstPtr &cloud)
Provide a target point cloud dataset (must contain XYZ data!)
void setInlierThreshold(double threshold)
Set the maximum distance between corresponding points.
void setMaximumIterations(int max_iterations)
Set the maximum number of iterations.
void getRemainingCorrespondences(const pcl::Correspondences &original_correspondences, pcl::Correspondences &remaining_correspondences) override
Get a list of valid correspondences after rejection from the original set of correspondences.
void setTargetPoints(pcl::PCLPointCloud2::ConstPtr cloud2) override
Method for setting the target cloud.
CorrespondencesConstPtr input_correspondences_
The input correspondences.
bool requiresTargetPoints() const override
See if this rejector requires a target cloud.
bool getRefineModel() const
Get the internal refine parameter value as set by the user using setRefineModel.
PointCloudConstPtr const getInputSource()
Get a pointer to the input point cloud dataset target.
std::string rejection_name_
The name of the rejection method.
PointCloudConstPtr const getInputTarget()
Get a pointer to the input point cloud dataset target.
void applyRejection(pcl::Correspondences &correspondences) override
Apply the rejection algorithm.
void getInliersIndices(pcl::Indices &inlier_indices)
Get the inlier indices found by the correspondence rejector.
void setSourcePoints(pcl::PCLPointCloud2::ConstPtr cloud2) override
Blob method for setting the source cloud.
void setRefineModel(const bool refine)
Specify whether the model should be refined internally using the variance of the inliers.
shared_ptr< CorrespondenceRejectorSampleConsensus< PointT > > Ptr
#define PCL_MAKE_ALIGNED_OPERATOR_NEW
Macro to signal a class requires a custom allocator.
Definition memory.h:63
Defines functions, macros and traits for allocating and using memory.
std::vector< pcl::Correspondence, Eigen::aligned_allocator< pcl::Correspondence > > Correspondences
IndicesAllocator<> Indices
Type used for indices in PCL.
Definition types.h:133
void fromPCLPointCloud2(const pcl::PCLPointCloud2 &msg, pcl::PointCloud< PointT > &cloud, const MsgFieldMap &field_map)
Convert a PCLPointCloud2 binary data blob into a pcl::PointCloud<T> object using a field_map.
shared_ptr< const ::pcl::PCLPointCloud2 > ConstPtr