Point Cloud Library (PCL)  1.12.1-dev
correspondence_estimation.h
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40 
41 #pragma once
42 
43 #include <pcl/common/io.h> // for getFields
44 #include <pcl/registration/correspondence_types.h>
45 #include <pcl/search/kdtree.h>
46 #include <pcl/memory.h>
47 #include <pcl/pcl_base.h>
48 #include <pcl/pcl_macros.h>
49 
50 #include <string>
51 
52 namespace pcl {
53 namespace registration {
54 /** \brief Abstract @b CorrespondenceEstimationBase class.
55  * All correspondence estimation methods should inherit from this.
56  * \author Radu B. Rusu
57  * \ingroup registration
58  */
59 template <typename PointSource, typename PointTarget, typename Scalar = float>
60 class CorrespondenceEstimationBase : public PCLBase<PointSource> {
61 public:
62  using Ptr =
63  shared_ptr<CorrespondenceEstimationBase<PointSource, PointTarget, Scalar>>;
64  using ConstPtr =
65  shared_ptr<const CorrespondenceEstimationBase<PointSource, PointTarget, Scalar>>;
66 
67  // using PCLBase<PointSource>::initCompute;
72 
74  using KdTreePtr = typename KdTree::Ptr;
75 
77  using KdTreeReciprocalPtr = typename KdTree::Ptr;
78 
82 
86 
88 
89  /** \brief Empty constructor. */
91  : corr_name_("CorrespondenceEstimationBase")
92  , tree_(new pcl::search::KdTree<PointTarget>)
93  , tree_reciprocal_(new pcl::search::KdTree<PointSource>)
94  , target_()
97  , target_cloud_updated_(true)
98  , source_cloud_updated_(true)
99  , force_no_recompute_(false)
101  {}
102 
103  /** \brief Empty destructor */
104  ~CorrespondenceEstimationBase() override = default;
105 
106  /** \brief Provide a pointer to the input source
107  * (e.g., the point cloud that we want to align to the target)
108  *
109  * \param[in] cloud the input point cloud source
110  */
111  inline void
113  {
114  source_cloud_updated_ = true;
116  input_fields_ = pcl::getFields<PointSource>();
117  }
118 
119  /** \brief Get a pointer to the input point cloud dataset target. */
120  inline PointCloudSourceConstPtr const
122  {
123  return (input_);
124  }
125 
126  /** \brief Provide a pointer to the input target
127  * (e.g., the point cloud that we want to align the input source to)
128  * \param[in] cloud the input point cloud target
129  */
130  inline void
132 
133  /** \brief Get a pointer to the input point cloud dataset target. */
134  inline PointCloudTargetConstPtr const
136  {
137  return (target_);
138  }
139 
140  /** \brief See if this rejector requires source normals */
141  virtual bool
143  {
144  return (false);
145  }
146 
147  /** \brief Abstract method for setting the source normals */
148  virtual void
150  {
151  PCL_WARN("[pcl::registration::%s::setSourceNormals] This class does not require "
152  "input source normals\n",
153  getClassName().c_str());
154  }
155 
156  /** \brief See if this rejector requires target normals */
157  virtual bool
159  {
160  return (false);
161  }
162 
163  /** \brief Abstract method for setting the target normals */
164  virtual void
166  {
167  PCL_WARN("[pcl::registration::%s::setTargetNormals] This class does not require "
168  "input target normals\n",
169  getClassName().c_str());
170  }
171 
172  /** \brief Provide a pointer to the vector of indices that represent the
173  * input source point cloud.
174  * \param[in] indices a pointer to the vector of indices
175  */
176  inline void
177  setIndicesSource(const IndicesPtr& indices)
178  {
179  setIndices(indices);
180  }
181 
182  /** \brief Get a pointer to the vector of indices used for the source dataset. */
183  inline IndicesPtr const
185  {
186  return (indices_);
187  }
188 
189  /** \brief Provide a pointer to the vector of indices that represent the input target
190  * point cloud. \param[in] indices a pointer to the vector of indices
191  */
192  inline void
193  setIndicesTarget(const IndicesPtr& indices)
194  {
195  target_cloud_updated_ = true;
196  target_indices_ = indices;
197  }
198 
199  /** \brief Get a pointer to the vector of indices used for the target dataset. */
200  inline IndicesPtr const
202  {
203  return (target_indices_);
204  }
205 
206  /** \brief Provide a pointer to the search object used to find correspondences in
207  * the target cloud.
208  * \param[in] tree a pointer to the spatial search object.
209  * \param[in] force_no_recompute If set to true, this tree will NEVER be
210  * recomputed, regardless of calls to setInputTarget. Only use if you are
211  * confident that the tree will be set correctly.
212  */
213  inline void
214  setSearchMethodTarget(const KdTreePtr& tree, bool force_no_recompute = false)
215  {
216  tree_ = tree;
217  force_no_recompute_ = force_no_recompute;
218  // Since we just set a new tree, we need to check for updates
219  target_cloud_updated_ = true;
220  }
221 
222  /** \brief Get a pointer to the search method used to find correspondences in the
223  * target cloud. */
224  inline KdTreePtr
226  {
227  return (tree_);
228  }
229 
230  /** \brief Provide a pointer to the search object used to find correspondences in
231  * the source cloud (usually used by reciprocal correspondence finding).
232  * \param[in] tree a pointer to the spatial search object.
233  * \param[in] force_no_recompute If set to true, this tree will NEVER be
234  * recomputed, regardless of calls to setInputSource. Only use if you are
235  * extremely confident that the tree will be set correctly.
236  */
237  inline void
239  bool force_no_recompute = false)
240  {
241  tree_reciprocal_ = tree;
242  force_no_recompute_reciprocal_ = force_no_recompute;
243  // Since we just set a new tree, we need to check for updates
244  source_cloud_updated_ = true;
245  }
246 
247  /** \brief Get a pointer to the search method used to find correspondences in the
248  * source cloud. */
249  inline KdTreeReciprocalPtr
251  {
252  return (tree_reciprocal_);
253  }
254 
255  /** \brief Determine the correspondences between input and target cloud.
256  * \param[out] correspondences the found correspondences (index of query point, index
257  * of target point, distance) \param[in] max_distance maximum allowed distance between
258  * correspondences
259  */
260  virtual void
262  pcl::Correspondences& correspondences,
263  double max_distance = std::numeric_limits<double>::max()) = 0;
264 
265  /** \brief Determine the reciprocal correspondences between input and target cloud.
266  * A correspondence is considered reciprocal if both Src_i has Tgt_i as a
267  * correspondence, and Tgt_i has Src_i as one.
268  *
269  * \param[out] correspondences the found correspondences (index of query and target
270  * point, distance) \param[in] max_distance maximum allowed distance between
271  * correspondences
272  */
273  virtual void
275  pcl::Correspondences& correspondences,
276  double max_distance = std::numeric_limits<double>::max()) = 0;
277 
278  /** \brief Provide a boost shared pointer to the PointRepresentation to be used
279  * when searching for nearest neighbors.
280  *
281  * \param[in] point_representation the PointRepresentation to be used by the
282  * k-D tree for nearest neighbor search
283  */
284  inline void
286  {
287  point_representation_ = point_representation;
288  }
289 
290  /** \brief Clone and cast to CorrespondenceEstimationBase */
292  clone() const = 0;
293 
294 protected:
295  /** \brief The correspondence estimation method name. */
296  std::string corr_name_;
297 
298  /** \brief A pointer to the spatial search object used for the target dataset. */
300 
301  /** \brief A pointer to the spatial search object used for the source dataset. */
303 
304  /** \brief The input point cloud dataset target. */
306 
307  /** \brief The target point cloud dataset indices. */
309 
310  /** \brief The point representation used (internal). */
312 
313  /** \brief The transformed input source point cloud dataset. */
315 
316  /** \brief The types of input point fields available. */
317  std::vector<pcl::PCLPointField> input_fields_;
318 
319  /** \brief Abstract class get name method. */
320  inline const std::string&
321  getClassName() const
322  {
323  return (corr_name_);
324  }
325 
326  /** \brief Internal computation initialization. */
327  bool
328  initCompute();
329 
330  /** \brief Internal computation initialization for reciprocal correspondences. */
331  bool
333 
334  /** \brief Variable that stores whether we have a new target cloud, meaning we need to
335  * pre-process it again. This way, we avoid rebuilding the kd-tree for the target
336  * cloud every time the determineCorrespondences () method is called. */
338  /** \brief Variable that stores whether we have a new source cloud, meaning we need to
339  * pre-process it again. This way, we avoid rebuilding the reciprocal kd-tree for the
340  * source cloud every time the determineCorrespondences () method is called. */
342  /** \brief A flag which, if set, means the tree operating on the target cloud
343  * will never be recomputed*/
345 
346  /** \brief A flag which, if set, means the tree operating on the source cloud
347  * will never be recomputed*/
349 };
350 
351 /** \brief @b CorrespondenceEstimation represents the base class for
352  * determining correspondences between target and query point
353  * sets/features.
354  *
355  * Code example:
356  *
357  * \code
358  * pcl::PointCloud<pcl::PointXYZRGBA>::Ptr source, target;
359  * // ... read or fill in source and target
360  * pcl::CorrespondenceEstimation<pcl::PointXYZ, pcl::PointXYZ> est;
361  * est.setInputSource (source);
362  * est.setInputTarget (target);
363  *
364  * pcl::Correspondences all_correspondences;
365  * // Determine all reciprocal correspondences
366  * est.determineReciprocalCorrespondences (all_correspondences);
367  * \endcode
368  *
369  * \author Radu B. Rusu, Michael Dixon, Dirk Holz
370  * \ingroup registration
371  */
372 template <typename PointSource, typename PointTarget, typename Scalar = float>
374 : public CorrespondenceEstimationBase<PointSource, PointTarget, Scalar> {
375 public:
376  using Ptr = shared_ptr<CorrespondenceEstimation<PointSource, PointTarget, Scalar>>;
377  using ConstPtr =
378  shared_ptr<const CorrespondenceEstimation<PointSource, PointTarget, Scalar>>;
379 
398 
400  using KdTreePtr = typename KdTree::Ptr;
401 
405 
409 
411 
412  /** \brief Empty constructor. */
413  CorrespondenceEstimation() { corr_name_ = "CorrespondenceEstimation"; }
414 
415  /** \brief Empty destructor */
416  ~CorrespondenceEstimation() override = default;
417 
418  /** \brief Determine the correspondences between input and target cloud.
419  * \param[out] correspondences the found correspondences (index of query point, index
420  * of target point, distance) \param[in] max_distance maximum allowed distance between
421  * correspondences
422  */
423  void
425  pcl::Correspondences& correspondences,
426  double max_distance = std::numeric_limits<double>::max()) override;
427 
428  /** \brief Determine the reciprocal correspondences between input and target cloud.
429  * A correspondence is considered reciprocal if both Src_i has Tgt_i as a
430  * correspondence, and Tgt_i has Src_i as one.
431  *
432  * \param[out] correspondences the found correspondences (index of query and target
433  * point, distance) \param[in] max_distance maximum allowed distance between
434  * correspondences
435  */
436  void
438  pcl::Correspondences& correspondences,
439  double max_distance = std::numeric_limits<double>::max()) override;
440 
441  /** \brief Clone and cast to CorrespondenceEstimationBase */
443  clone() const override
444  {
446  return (copy);
447  }
448 };
449 } // namespace registration
450 } // namespace pcl
451 
452 #include <pcl/registration/impl/correspondence_estimation.hpp>
PCL base class.
Definition: pcl_base.h:70
PointCloudConstPtr input_
The input point cloud dataset.
Definition: pcl_base.h:147
virtual void setInputCloud(const PointCloudConstPtr &cloud)
Provide a pointer to the input dataset.
Definition: pcl_base.hpp:65
IndicesPtr indices_
A pointer to the vector of point indices to use.
Definition: pcl_base.h:150
virtual void setIndices(const IndicesPtr &indices)
Provide a pointer to the vector of indices that represents the input data.
Definition: pcl_base.hpp:72
shared_ptr< PointCloud< PointSource > > Ptr
Definition: point_cloud.h:413
shared_ptr< const PointCloud< PointSource > > ConstPtr
Definition: point_cloud.h:414
Abstract CorrespondenceEstimationBase class.
typename KdTree::PointRepresentationConstPtr PointRepresentationConstPtr
PointCloudTargetPtr input_transformed_
The transformed input source point cloud dataset.
void setSearchMethodSource(const KdTreeReciprocalPtr &tree, bool force_no_recompute=false)
Provide a pointer to the search object used to find correspondences in the source cloud (usually used...
PointCloudTargetConstPtr target_
The input point cloud dataset target.
PointCloudTargetConstPtr const getInputTarget()
Get a pointer to the input point cloud dataset target.
shared_ptr< const CorrespondenceEstimationBase< PointSource, PointTarget, Scalar > > ConstPtr
bool initCompute()
Internal computation initialization.
virtual void determineReciprocalCorrespondences(pcl::Correspondences &correspondences, double max_distance=std::numeric_limits< double >::max())=0
Determine the reciprocal correspondences between input and target cloud.
IndicesPtr const getIndicesTarget()
Get a pointer to the vector of indices used for the target dataset.
const std::string & getClassName() const
Abstract class get name method.
void setPointRepresentation(const PointRepresentationConstPtr &point_representation)
Provide a boost shared pointer to the PointRepresentation to be used when searching for nearest neigh...
bool source_cloud_updated_
Variable that stores whether we have a new source cloud, meaning we need to pre-process it again.
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.
virtual void setSourceNormals(pcl::PCLPointCloud2::ConstPtr)
Abstract method for setting the source normals.
typename PointCloudTarget::ConstPtr PointCloudTargetConstPtr
KdTreeReciprocalPtr getSearchMethodSource() const
Get a pointer to the search method used to find correspondences in the source cloud.
PointRepresentationConstPtr point_representation_
The point representation used (internal).
IndicesPtr const getIndicesSource()
Get a pointer to the vector of indices used for the source dataset.
void setInputSource(const PointCloudSourceConstPtr &cloud)
Provide a pointer to the input source (e.g., the point cloud that we want to align to the target)
virtual bool requiresTargetNormals() const
See if this rejector requires target normals.
std::vector< pcl::PCLPointField > input_fields_
The types of input point fields available.
virtual bool requiresSourceNormals() const
See if this rejector requires source normals.
std::string corr_name_
The correspondence estimation method name.
void setInputTarget(const PointCloudTargetConstPtr &cloud)
Provide a pointer to the input target (e.g., the point cloud that we want to align the input source t...
virtual CorrespondenceEstimationBase< PointSource, PointTarget, Scalar >::Ptr clone() const =0
Clone and cast to CorrespondenceEstimationBase.
bool target_cloud_updated_
Variable that stores whether we have a new target cloud, meaning we need to pre-process it again.
void setIndicesSource(const IndicesPtr &indices)
Provide a pointer to the vector of indices that represent the input source point cloud.
KdTreePtr tree_
A pointer to the spatial search object used for the target dataset.
PointCloudSourceConstPtr const getInputSource()
Get a pointer to the input point cloud dataset target.
KdTreeReciprocalPtr tree_reciprocal_
A pointer to the spatial search object used for the source dataset.
virtual void setTargetNormals(pcl::PCLPointCloud2::ConstPtr)
Abstract method for setting the target normals.
virtual void determineCorrespondences(pcl::Correspondences &correspondences, double max_distance=std::numeric_limits< double >::max())=0
Determine the correspondences between input and target cloud.
~CorrespondenceEstimationBase() override=default
Empty destructor.
bool initComputeReciprocal()
Internal computation initialization for reciprocal correspondences.
bool force_no_recompute_reciprocal_
A flag which, if set, means the tree operating on the source cloud will never be recomputed.
IndicesPtr target_indices_
The target point cloud dataset indices.
void setIndicesTarget(const IndicesPtr &indices)
Provide a pointer to the vector of indices that represent the input target point cloud.
typename PointCloudSource::ConstPtr PointCloudSourceConstPtr
shared_ptr< CorrespondenceEstimationBase< PointSource, PointTarget, Scalar > > Ptr
bool force_no_recompute_
A flag which, if set, means the tree operating on the target cloud will never be recomputed.
KdTreePtr getSearchMethodTarget() const
Get a pointer to the search method used to find correspondences in the target cloud.
CorrespondenceEstimation represents the base class for determining correspondences between target and...
void determineCorrespondences(pcl::Correspondences &correspondences, double max_distance=std::numeric_limits< double >::max()) override
Determine the correspondences between input and target cloud.
CorrespondenceEstimationBase< PointSource, PointTarget, Scalar >::Ptr clone() const override
Clone and cast to CorrespondenceEstimationBase.
typename PointCloudSource::ConstPtr PointCloudSourceConstPtr
shared_ptr< CorrespondenceEstimation< PointSource, PointTarget, Scalar > > Ptr
void determineReciprocalCorrespondences(pcl::Correspondences &correspondences, double max_distance=std::numeric_limits< double >::max()) override
Determine the reciprocal correspondences between input and target cloud.
shared_ptr< const CorrespondenceEstimation< PointSource, PointTarget, Scalar > > ConstPtr
typename KdTree::PointRepresentationConstPtr PointRepresentationConstPtr
~CorrespondenceEstimation() override=default
Empty destructor.
typename PointCloudTarget::ConstPtr PointCloudTargetConstPtr
search::KdTree is a wrapper class which inherits the pcl::KdTree class for performing search function...
Definition: kdtree.h:62
shared_ptr< KdTree< PointT, Tree > > Ptr
Definition: kdtree.h:75
typename PointRepresentation< PointT >::ConstPtr PointRepresentationConstPtr
Definition: kdtree.h:80
Defines functions, macros and traits for allocating and using memory.
std::vector< pcl::Correspondence, Eigen::aligned_allocator< pcl::Correspondence > > Correspondences
shared_ptr< Indices > IndicesPtr
Definition: pcl_base.h:58
Defines all the PCL and non-PCL macros used.
shared_ptr< const ::pcl::PCLPointCloud2 > ConstPtr