Point Cloud Library (PCL)  1.10.1-dev
correspondence_rejection_sample_consensus.h
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40 
41 #pragma once
42 
43 
44 #include <pcl/memory.h>
45 #include <pcl/pcl_macros.h>
46 #include <pcl/registration/correspondence_rejection.h>
47 
48 #include <pcl/sample_consensus/ransac.h>
49 #include <pcl/sample_consensus/sac_model_registration.h>
50 #include <pcl/common/transforms.h>
51 
52 namespace pcl
53 {
54  namespace registration
55  {
56  /** \brief CorrespondenceRejectorSampleConsensus implements a correspondence rejection
57  * using Random Sample Consensus to identify inliers (and reject outliers)
58  * \author Dirk Holz
59  * \ingroup registration
60  */
61  template <typename PointT>
63  {
65  using PointCloudPtr = typename PointCloud::Ptr;
66  using PointCloudConstPtr = typename PointCloud::ConstPtr;
67 
68  public:
72 
75 
76  /** \brief Empty constructor. Sets the inlier threshold to 5cm (0.05m),
77  * and the maximum number of iterations to 1000.
78  */
80  : inlier_threshold_ (0.05)
81  , max_iterations_ (1000) // std::numeric_limits<int>::max ()
82  , input_ ()
84  , target_ ()
85  , refine_ (false)
86  , save_inliers_ (false)
87  {
88  rejection_name_ = "CorrespondenceRejectorSampleConsensus";
89  }
90 
91  /** \brief Empty destructor. */
93 
94  /** \brief Get a list of valid correspondences after rejection from the original set of correspondences.
95  * \param[in] original_correspondences the set of initial correspondences given
96  * \param[out] remaining_correspondences the resultant filtered set of remaining correspondences
97  */
98  inline void
99  getRemainingCorrespondences (const pcl::Correspondences& original_correspondences,
100  pcl::Correspondences& remaining_correspondences) override;
101 
102  /** \brief Provide a source point cloud dataset (must contain XYZ data!)
103  * \param[in] cloud a cloud containing XYZ data
104  */
105  virtual inline void
106  setInputSource (const PointCloudConstPtr &cloud)
107  {
108  input_ = cloud;
109  }
110 
111  /** \brief Get a pointer to the input point cloud dataset target. */
112  inline PointCloudConstPtr const
113  getInputSource () { return (input_); }
114 
115  /** \brief Provide a target point cloud dataset (must contain XYZ data!)
116  * \param[in] cloud a cloud containing XYZ data
117  */
118  virtual inline void
119  setInputTarget (const PointCloudConstPtr &cloud) { target_ = cloud; }
120 
121  /** \brief Get a pointer to the input point cloud dataset target. */
122  inline PointCloudConstPtr const
123  getInputTarget () { return (target_ ); }
124 
125 
126  /** \brief See if this rejector requires source points */
127  bool
128  requiresSourcePoints () const override
129  { return (true); }
130 
131  /** \brief Blob method for setting the source cloud */
132  void
134  {
135  PointCloudPtr cloud (new PointCloud);
136  fromPCLPointCloud2 (*cloud2, *cloud);
137  setInputSource (cloud);
138  }
139 
140  /** \brief See if this rejector requires a target cloud */
141  bool
142  requiresTargetPoints () const override
143  { return (true); }
144 
145  /** \brief Method for setting the target cloud */
146  void
148  {
149  PointCloudPtr cloud (new PointCloud);
150  fromPCLPointCloud2 (*cloud2, *cloud);
151  setInputTarget (cloud);
152  }
153 
154  /** \brief Set the maximum distance between corresponding points.
155  * Correspondences with distances below the threshold are considered as inliers.
156  * \param[in] threshold Distance threshold in the same dimension as source and target data sets.
157  */
158  inline void
159  setInlierThreshold (double threshold) { inlier_threshold_ = threshold; };
160 
161  /** \brief Get the maximum distance between corresponding points.
162  * \return Distance threshold in the same dimension as source and target data sets.
163  */
164  inline double
166 
167  /** \brief Set the maximum number of iterations.
168  * \param[in] max_iterations Maximum number if iterations to run
169  */
170  inline void
171  setMaximumIterations (int max_iterations) { max_iterations_ = std::max (max_iterations, 0); }
172 
173  /** \brief Get the maximum number of iterations.
174  * \return max_iterations Maximum number if iterations to run
175  */
176  inline int
178 
179  /** \brief Get the best transformation after RANSAC rejection.
180  * \return The homogeneous 4x4 transformation yielding the largest number of inliers.
181  */
182  inline Eigen::Matrix4f
184 
185  /** \brief Specify whether the model should be refined internally using the variance of the inliers
186  * \param[in] refine true if the model should be refined, false otherwise
187  */
188  inline void
189  setRefineModel (const bool refine)
190  {
191  refine_ = refine;
192  }
193 
194  /** \brief Get the internal refine parameter value as set by the user using setRefineModel */
195  inline bool
196  getRefineModel () const
197  {
198  return (refine_);
199  }
200 
201  /** \brief Get the inlier indices found by the correspondence rejector. This information is only saved if setSaveInliers(true) was called in advance.
202  * \param[out] inlier_indices Indices for the inliers
203  */
204  inline void
205  getInliersIndices (std::vector<int> &inlier_indices) { inlier_indices = inlier_indices_; }
206 
207  /** \brief Set whether to save inliers or not
208  * \param[in] s True to save inliers / False otherwise
209  */
210  inline void
211  setSaveInliers (bool s) { save_inliers_ = s; }
212 
213  /** \brief Get whether the rejector is configured to save inliers */
214  inline bool
216 
217 
218  protected:
219 
220  /** \brief Apply the rejection algorithm.
221  * \param[out] correspondences the set of resultant correspondences.
222  */
223  inline void
224  applyRejection (pcl::Correspondences &correspondences) override
225  {
227  }
228 
230 
232 
233  PointCloudConstPtr input_;
234  PointCloudPtr input_transformed_;
235  PointCloudConstPtr target_;
236 
237  Eigen::Matrix4f best_transformation_;
238 
239  bool refine_;
240  std::vector<int> inlier_indices_;
242 
243  public:
245  };
246  }
247 }
248 
249 #include <pcl/registration/impl/correspondence_rejection_sample_consensus.hpp>
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...
Definition: conversions.h:168
shared_ptr< const CorrespondenceRejector > ConstPtr
double getInlierThreshold()
Get the maximum distance between corresponding points.
shared_ptr< PointCloud< PointT > > Ptr
Definition: point_cloud.h:414
Defines functions, macros and traits for allocating and using memory.
shared_ptr< CorrespondenceRejector > Ptr
CorrespondenceRejector represents the base class for correspondence rejection methods ...
shared_ptr< const ::pcl::PCLPointCloud2 > ConstPtr
void setTargetPoints(pcl::PCLPointCloud2::ConstPtr cloud2) override
Method for setting the target cloud.
void getInliersIndices(std::vector< int > &inlier_indices)
Get the inlier indices found by the correspondence rejector.
bool requiresTargetPoints() const override
See if this rejector requires a target cloud.
#define PCL_MAKE_ALIGNED_OPERATOR_NEW
Macro to signal a class requires a custom allocator.
Definition: memory.h:65
const std::string & getClassName() const
Get a string representation of the name of this class.
Eigen::Matrix4f getBestTransformation()
Get the best transformation after RANSAC rejection.
void applyRejection(pcl::Correspondences &correspondences) override
Apply the rejection algorithm.
virtual void setInputTarget(const PointCloudConstPtr &cloud)
Provide a target point cloud dataset (must contain XYZ data!)
void setMaximumIterations(int max_iterations)
Set the maximum number of iterations.
PointCloudConstPtr const getInputSource()
Get a pointer to the input point cloud dataset target.
bool requiresSourcePoints() const override
See if this rejector requires source points.
void setInlierThreshold(double threshold)
Set the maximum distance between corresponding points.
bool getRefineModel() const
Get the internal refine parameter value as set by the user using setRefineModel.
PointCloud represents the base class in PCL for storing collections of 3D points. ...
CorrespondenceRejectorSampleConsensus implements a correspondence rejection using Random Sample Conse...
PointCloudConstPtr const getInputTarget()
Get a pointer to the input point cloud dataset target.
CorrespondencesConstPtr input_correspondences_
The input correspondences.
shared_ptr< const PointCloud< PointT > > ConstPtr
Definition: point_cloud.h:415
virtual void setInputSource(const PointCloudConstPtr &cloud)
Provide a source point cloud dataset (must contain XYZ data!)
std::string rejection_name_
The name of the rejection method.
std::vector< pcl::Correspondence, Eigen::aligned_allocator< pcl::Correspondence > > Correspondences
bool getSaveInliers()
Get whether the rejector is configured to save inliers.
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.
boost::shared_ptr< T > shared_ptr
Alias for boost::shared_ptr.
Definition: memory.h:81
void setRefineModel(const bool refine)
Specify whether the model should be refined internally using the variance of the inliers.
void setSourcePoints(pcl::PCLPointCloud2::ConstPtr cloud2) override
Blob method for setting the source cloud.
Defines all the PCL and non-PCL macros used.