Point Cloud Library (PCL)  1.9.1-dev
correspondence_rejection.h
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40 
41 #pragma once
42 
43 #include <pcl/registration/correspondence_types.h>
44 #include <pcl/registration/correspondence_sorting.h>
45 #include <pcl/console/print.h>
46 #include <pcl/common/transforms.h>
47 #include <pcl/point_cloud.h>
48 #include <pcl/search/kdtree.h>
49 
50 namespace pcl
51 {
52  namespace registration
53  {
54  /** @b CorrespondenceRejector represents the base class for correspondence rejection methods
55  * \author Dirk Holz
56  * \ingroup registration
57  */
59  {
60  public:
61  using Ptr = boost::shared_ptr<CorrespondenceRejector>;
62  using ConstPtr = boost::shared_ptr<const CorrespondenceRejector>;
63 
64  /** \brief Empty constructor. */
66  {}
67 
68  /** \brief Empty destructor. */
70 
71  /** \brief Provide a pointer to the vector of the input correspondences.
72  * \param[in] correspondences the const boost shared pointer to a correspondence vector
73  */
74  virtual inline void
76  {
77  input_correspondences_ = correspondences;
78  };
79 
80  /** \brief Get a pointer to the vector of the input correspondences.
81  * \return correspondences the const boost shared pointer to a correspondence vector
82  */
85 
86  /** \brief Run correspondence rejection
87  * \param[out] correspondences Vector of correspondences that have not been rejected.
88  */
89  inline void
91  {
93  return;
94 
95  applyRejection (correspondences);
96  }
97 
98  /** \brief Get a list of valid correspondences after rejection from the original set of correspondences.
99  * Pure virtual. Compared to \a getCorrespondences this function is
100  * stateless, i.e., input correspondences do not need to be provided beforehand,
101  * but are directly provided in the function call.
102  * \param[in] original_correspondences the set of initial correspondences given
103  * \param[out] remaining_correspondences the resultant filtered set of remaining correspondences
104  */
105  virtual inline void
106  getRemainingCorrespondences (const pcl::Correspondences& original_correspondences,
107  pcl::Correspondences& remaining_correspondences) = 0;
108 
109  /** \brief Determine the indices of query points of
110  * correspondences that have been rejected, i.e., the difference
111  * between the input correspondences (set via \a setInputCorrespondences)
112  * and the given correspondence vector.
113  * \param[in] correspondences Vector of correspondences after rejection
114  * \param[out] indices Vector of query point indices of those correspondences
115  * that have been rejected.
116  */
117  inline void
119  std::vector<int>& indices)
120  {
122  {
123  PCL_WARN ("[pcl::registration::%s::getRejectedQueryIndices] Input correspondences not set (lookup of rejected correspondences _not_ possible).\n", getClassName ().c_str ());
124  return;
125  }
126 
127  pcl::getRejectedQueryIndices(*input_correspondences_, correspondences, indices);
128  }
129 
130  /** \brief Get a string representation of the name of this class. */
131  inline const std::string&
132  getClassName () const { return (rejection_name_); }
133 
134 
135  /** \brief See if this rejector requires source points */
136  virtual bool
138  { return (false); }
139 
140  /** \brief Abstract method for setting the source cloud */
141  virtual void
143  {
144  PCL_WARN ("[pcl::registration::%s::setSourcePoints] This class does not require an input source cloud", getClassName ().c_str ());
145  }
146 
147  /** \brief See if this rejector requires source normals */
148  virtual bool
150  { return (false); }
151 
152  /** \brief Abstract method for setting the source normals */
153  virtual void
155  {
156  PCL_WARN ("[pcl::registration::%s::setSourceNormals] This class does not require input source normals", getClassName ().c_str ());
157  }
158  /** \brief See if this rejector requires a target cloud */
159  virtual bool
161  { return (false); }
162 
163  /** \brief Abstract method for setting the target cloud */
164  virtual void
166  {
167  PCL_WARN ("[pcl::registration::%s::setTargetPoints] This class does not require an input target cloud", getClassName ().c_str ());
168  }
169 
170  /** \brief See if this rejector requires target normals */
171  virtual bool
173  { return (false); }
174 
175  /** \brief Abstract method for setting the target normals */
176  virtual void
178  {
179  PCL_WARN ("[pcl::registration::%s::setTargetNormals] This class does not require input target normals", getClassName ().c_str ());
180  }
181 
182  protected:
183 
184  /** \brief The name of the rejection method. */
185  std::string rejection_name_;
186 
187  /** \brief The input correspondences. */
189 
190  /** \brief Abstract rejection method. */
191  virtual void
192  applyRejection (Correspondences &correspondences) = 0;
193  };
194 
195  /** @b DataContainerInterface provides a generic interface for computing correspondence scores between correspondent
196  * points in the input and target clouds
197  * \ingroup registration
198  */
200  {
201  public:
202  using Ptr = boost::shared_ptr<DataContainerInterface>;
203  using ConstPtr = boost::shared_ptr<const DataContainerInterface>;
204 
205  virtual ~DataContainerInterface () = default;
206  virtual double getCorrespondenceScore (int index) = 0;
207  virtual double getCorrespondenceScore (const pcl::Correspondence &) = 0;
208  virtual double getCorrespondenceScoreFromNormals (const pcl::Correspondence &) = 0;
209  };
210 
211  /** @b DataContainer is a container for the input and target point clouds and implements the interface
212  * to compute correspondence scores between correspondent points in the input and target clouds
213  * \ingroup registration
214  */
215  template <typename PointT, typename NormalT = pcl::PointNormal>
217  {
219  using PointCloudPtr = typename PointCloud::Ptr;
220  using PointCloudConstPtr = typename PointCloud::ConstPtr;
221 
222  using KdTreePtr = typename pcl::search::KdTree<PointT>::Ptr;
223 
225  using NormalsPtr = typename Normals::Ptr;
226  using NormalsConstPtr = typename Normals::ConstPtr;
227 
228  public:
229 
230  /** \brief Empty constructor. */
231  DataContainer (bool needs_normals = false)
232  : input_ ()
233  , input_transformed_ ()
234  , target_ ()
235  , input_normals_ ()
236  , input_normals_transformed_ ()
237  , target_normals_ ()
238  , tree_ (new pcl::search::KdTree<PointT>)
239  , class_name_ ("DataContainer")
240  , needs_normals_ (needs_normals)
241  , target_cloud_updated_ (true)
242  , force_no_recompute_ (false)
243  {
244  }
245 
246  /** \brief Empty destructor */
248 
249  /** \brief Provide a source point cloud dataset (must contain XYZ
250  * data!), used to compute the correspondence distance.
251  * \param[in] cloud a cloud containing XYZ data
252  */
253  inline void
254  setInputSource (const PointCloudConstPtr &cloud)
255  {
256  input_ = cloud;
257  }
258 
259  /** \brief Get a pointer to the input point cloud dataset target. */
260  inline PointCloudConstPtr const
261  getInputSource () { return (input_); }
262 
263  /** \brief Provide a target point cloud dataset (must contain XYZ
264  * data!), used to compute the correspondence distance.
265  * \param[in] target a cloud containing XYZ data
266  */
267  inline void
268  setInputTarget (const PointCloudConstPtr &target)
269  {
270  target_ = target;
271  target_cloud_updated_ = true;
272  }
273 
274  /** \brief Get a pointer to the input point cloud dataset target. */
275  inline PointCloudConstPtr const
276  getInputTarget () { return (target_); }
277 
278  /** \brief Provide a pointer to the search object used to find correspondences in
279  * the target cloud.
280  * \param[in] tree a pointer to the spatial search object.
281  * \param[in] force_no_recompute If set to true, this tree will NEVER be
282  * recomputed, regardless of calls to setInputTarget. Only use if you are
283  * confident that the tree will be set correctly.
284  */
285  inline void
286  setSearchMethodTarget (const KdTreePtr &tree,
287  bool force_no_recompute = false)
288  {
289  tree_ = tree;
290  if (force_no_recompute)
291  {
292  force_no_recompute_ = true;
293  }
294  target_cloud_updated_ = true;
295  }
296 
297  /** \brief Set the normals computed on the input point cloud
298  * \param[in] normals the normals computed for the input cloud
299  */
300  inline void
301  setInputNormals (const NormalsConstPtr &normals) { input_normals_ = normals; }
302 
303  /** \brief Get the normals computed on the input point cloud */
304  inline NormalsConstPtr
305  getInputNormals () { return (input_normals_); }
306 
307  /** \brief Set the normals computed on the target point cloud
308  * \param[in] normals the normals computed for the input cloud
309  */
310  inline void
311  setTargetNormals (const NormalsConstPtr &normals) { target_normals_ = normals; }
312 
313  /** \brief Get the normals computed on the target point cloud */
314  inline NormalsConstPtr
315  getTargetNormals () { return (target_normals_); }
316 
317  /** \brief Get the correspondence score for a point in the input cloud
318  * \param[in] index index of the point in the input cloud
319  */
320  inline double
321  getCorrespondenceScore (int index) override
322  {
323  if ( target_cloud_updated_ && !force_no_recompute_ )
324  {
325  tree_->setInputCloud (target_);
326  }
327  std::vector<int> indices (1);
328  std::vector<float> distances (1);
329  if (tree_->nearestKSearch (input_->points[index], 1, indices, distances))
330  return (distances[0]);
331  return (std::numeric_limits<double>::max ());
332  }
333 
334  /** \brief Get the correspondence score for a given pair of correspondent points
335  * \param[in] corr Correspondent points
336  */
337  inline double
339  {
340  // Get the source and the target feature from the list
341  const PointT &src = input_->points[corr.index_query];
342  const PointT &tgt = target_->points[corr.index_match];
343 
344  return ((src.getVector4fMap () - tgt.getVector4fMap ()).squaredNorm ());
345  }
346 
347  /** \brief Get the correspondence score for a given pair of correspondent points based on
348  * the angle between the normals. The normmals for the in put and target clouds must be
349  * set before using this function
350  * \param[in] corr Correspondent points
351  */
352  inline double
354  {
355  //assert ( (input_normals_->points.size () != 0) && (target_normals_->points.size () != 0) && "Normals are not set for the input and target point clouds");
356  assert (input_normals_ && target_normals_ && "Normals are not set for the input and target point clouds");
357  const NormalT &src = input_normals_->points[corr.index_query];
358  const NormalT &tgt = target_normals_->points[corr.index_match];
359  return (double ((src.normal[0] * tgt.normal[0]) + (src.normal[1] * tgt.normal[1]) + (src.normal[2] * tgt.normal[2])));
360  }
361 
362  private:
363  /** \brief The input point cloud dataset */
364  PointCloudConstPtr input_;
365 
366  /** \brief The input transformed point cloud dataset */
367  PointCloudPtr input_transformed_;
368 
369  /** \brief The target point cloud datase. */
370  PointCloudConstPtr target_;
371 
372  /** \brief Normals to the input point cloud */
373  NormalsConstPtr input_normals_;
374 
375  /** \brief Normals to the input point cloud */
376  NormalsPtr input_normals_transformed_;
377 
378  /** \brief Normals to the target point cloud */
379  NormalsConstPtr target_normals_;
380 
381  /** \brief A pointer to the spatial search object. */
382  KdTreePtr tree_;
383 
384  /** \brief The name of the rejection method. */
385  std::string class_name_;
386 
387  /** \brief Should the current data container use normals? */
388  bool needs_normals_;
389 
390  /** \brief Variable that stores whether we have a new target cloud, meaning we need to pre-process it again.
391  * This way, we avoid rebuilding the kd-tree */
392  bool target_cloud_updated_;
393 
394  /** \brief A flag which, if set, means the tree operating on the target cloud
395  * will never be recomputed*/
396  bool force_no_recompute_;
397 
398 
399 
400  /** \brief Get a string representation of the name of this class. */
401  inline const std::string&
402  getClassName () const { return (class_name_); }
403  };
404  }
405 }
A point structure representing normal coordinates and the surface curvature estimate.
double getCorrespondenceScoreFromNormals(const pcl::Correspondence &corr) override
Get the correspondence score for a given pair of correspondent points based on the angle between the ...
virtual bool requiresTargetNormals() const
See if this rejector requires target normals.
DataContainer is a container for the input and target point clouds and implements the interface to co...
void setSearchMethodTarget(const KdTreePtr &tree, bool force_no_recompute=false)
Provide a pointer to the search object used to find correspondences in the target cloud...
int index_match
Index of the matching (target) point.
DataContainerInterface provides a generic interface for computing correspondence scores between corre...
double getCorrespondenceScore(int index) override
Get the correspondence score for a point in the input cloud.
virtual void setInputCorrespondences(const CorrespondencesConstPtr &correspondences)
Provide a pointer to the vector of the input correspondences.
This file defines compatibility wrappers for low level I/O functions.
Definition: convolution.h:45
CorrespondenceRejector represents the base class for correspondence rejection methods ...
virtual void getRemainingCorrespondences(const pcl::Correspondences &original_correspondences, pcl::Correspondences &remaining_correspondences)=0
Get a list of valid correspondences after rejection from the original set of correspondences.
double getCorrespondenceScore(const pcl::Correspondence &corr) override
Get the correspondence score for a given pair of correspondent points.
virtual bool requiresSourcePoints() const
See if this rejector requires source points.
void getCorrespondences(pcl::Correspondences &correspondences)
Run correspondence rejection.
Correspondence represents a match between two entities (e.g., points, descriptors, etc).
const std::string & getClassName() const
Get a string representation of the name of this class.
DataContainer(bool needs_normals=false)
Empty constructor.
boost::shared_ptr< DataContainerInterface > Ptr
PointCloudConstPtr const getInputSource()
Get a pointer to the input point cloud dataset target.
int index_query
Index of the query (source) point.
virtual void setTargetPoints(pcl::PCLPointCloud2::ConstPtr)
Abstract method for setting the target cloud.
CorrespondencesConstPtr getInputCorrespondences()
Get a pointer to the vector of the input correspondences.
void setInputNormals(const NormalsConstPtr &normals)
Set the normals computed on the input point cloud.
boost::shared_ptr< const Correspondences > CorrespondencesConstPtr
void setInputSource(const PointCloudConstPtr &cloud)
Provide a source point cloud dataset (must contain XYZ data!), used to compute the correspondence dis...
boost::shared_ptr< KdTree< PointT, Tree > > Ptr
Definition: kdtree.h:78
boost::shared_ptr< PointCloud< PointT > > Ptr
Definition: point_cloud.h:415
PointCloud represents the base class in PCL for storing collections of 3D points. ...
boost::shared_ptr< const DataContainerInterface > ConstPtr
void getRejectedQueryIndices(const pcl::Correspondences &correspondences_before, const pcl::Correspondences &correspondences_after, std::vector< int > &indices, bool presorting_required=true)
Get the query points of correspondences that are present in one correspondence vector but not in the ...
NormalsConstPtr getInputNormals()
Get the normals computed on the input point cloud.
virtual void setSourcePoints(pcl::PCLPointCloud2::ConstPtr)
Abstract method for setting the source cloud.
boost::shared_ptr< const PointCloud< PointT > > ConstPtr
Definition: point_cloud.h:416
boost::shared_ptr< CorrespondenceRejector > Ptr
CorrespondencesConstPtr input_correspondences_
The input correspondences.
void setInputTarget(const PointCloudConstPtr &target)
Provide a target point cloud dataset (must contain XYZ data!), used to compute the correspondence dis...
virtual void setSourceNormals(pcl::PCLPointCloud2::ConstPtr)
Abstract method for setting the source normals.
std::string rejection_name_
The name of the rejection method.
void getRejectedQueryIndices(const pcl::Correspondences &correspondences, std::vector< int > &indices)
Determine the indices of query points of correspondences that have been rejected, i...
std::vector< pcl::Correspondence, Eigen::aligned_allocator< pcl::Correspondence > > Correspondences
virtual void applyRejection(Correspondences &correspondences)=0
Abstract rejection method.
void setTargetNormals(const NormalsConstPtr &normals)
Set the normals computed on the target point cloud.
A point structure representing Euclidean xyz coordinates, and the RGB color.
boost::shared_ptr< const ::pcl::PCLPointCloud2 > ConstPtr
virtual bool requiresTargetPoints() const
See if this rejector requires a target cloud.
NormalsConstPtr getTargetNormals()
Get the normals computed on the target point cloud.
virtual bool requiresSourceNormals() const
See if this rejector requires source normals.
virtual void setTargetNormals(pcl::PCLPointCloud2::ConstPtr)
Abstract method for setting the target normals.
KdTree represents the base spatial locator class for kd-tree implementations.
Definition: kdtree.h:55
boost::shared_ptr< const CorrespondenceRejector > ConstPtr
PointCloudConstPtr const getInputTarget()
Get a pointer to the input point cloud dataset target.