Point Cloud Library (PCL)  1.14.1-dev
transformation_validation_euclidean.h
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40 
41 #pragma once
42 
43 #include <pcl/kdtree/kdtree.h>
44 #include <pcl/registration/transformation_validation.h>
45 #include <pcl/search/kdtree.h>
46 #include <pcl/memory.h>
47 #include <pcl/pcl_macros.h>
48 #include <pcl/point_representation.h>
49 
50 namespace pcl {
51 namespace registration {
52 /** \brief TransformationValidationEuclidean computes an L2SQR norm between a source and
53  * target dataset.
54  *
55  * To prevent points with bad correspondences to contribute to the overall score, the
56  * class also accepts a maximum_range parameter given via \ref setMaxRange that is used
57  * as a cutoff value for nearest neighbor distance comparisons.
58  *
59  * The output score is normalized with respect to the number of valid correspondences
60  * found.
61  *
62  * Usage example:
63  * \code
64  * pcl::TransformationValidationEuclidean<pcl::PointXYZ, pcl::PointXYZ> tve;
65  * tve.setMaxRange (0.01); // 1cm
66  * double score = tve.validateTransformation (source, target, transformation);
67  * \endcode
68  *
69  * \note The class is templated on the source and target point types as well as on the
70  * output scalar of the transformation matrix (i.e., float or double). Default: float.
71  * \author Radu B. Rusu
72  * \ingroup registration
73  */
74 template <typename PointSource, typename PointTarget, typename Scalar = float>
76 public:
77  using Matrix4 =
79 
80  using Ptr = shared_ptr<TransformationValidation<PointSource, PointTarget, Scalar>>;
81  using ConstPtr =
82  shared_ptr<const TransformationValidation<PointSource, PointTarget, Scalar>>;
83 
85  using KdTreePtr = typename KdTree::Ptr;
86 
88 
90  typename TransformationValidation<PointSource,
91  PointTarget>::PointCloudSourceConstPtr;
93  typename TransformationValidation<PointSource,
94  PointTarget>::PointCloudTargetConstPtr;
95 
96  /** \brief Constructor.
97  * Sets the \a max_range parameter to double::max, \a threshold_ to NaN
98  * and initializes the internal search \a tree to a FLANN kd-tree.
99  */
101  : max_range_(std::numeric_limits<double>::max())
102  , threshold_(std::numeric_limits<double>::quiet_NaN())
103  , tree_(new pcl::search::KdTree<PointTarget>)
104  {}
105 
107 
108  /** \brief Set the maximum allowable distance between a point and its correspondence
109  * in the target in order for a correspondence to be considered \a valid. Default:
110  * double::max. \param[in] max_range the new maximum allowable distance
111  */
112  inline void
113  setMaxRange(double max_range)
114  {
115  max_range_ = max_range;
116  }
117 
118  /** \brief Get the maximum allowable distance between a point and its
119  * correspondence, as set by the user.
120  */
121  inline double
123  {
124  return (max_range_);
125  }
126 
127  /** \brief Provide a pointer to the search object used to find correspondences in
128  * the target cloud.
129  * \param[in] tree a pointer to the spatial search object.
130  * \param[in] force_no_recompute If set to true, this tree will NEVER be
131  * recomputed, regardless of calls to setInputTarget. Only use if you are
132  * confident that the tree will be set correctly.
133  */
134  inline void
135  setSearchMethodTarget(const KdTreePtr& tree, bool force_no_recompute = false)
136  {
137  tree_ = tree;
138  force_no_recompute_ = force_no_recompute;
139  }
140 
141  /** \brief Set a threshold for which a specific transformation is considered valid.
142  *
143  * \note Since we're using MSE (Mean Squared Error) as a metric, the threshold
144  * represents the mean Euclidean distance threshold over all nearest neighbors
145  * up to max_range.
146  *
147  * \param[in] threshold the threshold for which a transformation is vali
148  */
149  inline void
150  setThreshold(double threshold)
151  {
152  threshold_ = threshold;
153  }
154 
155  /** \brief Get the threshold for which a specific transformation is valid. */
156  inline double
158  {
159  return (threshold_);
160  }
161 
162  /** \brief Validate the given transformation with respect to the input cloud data, and
163  * return a score.
164  *
165  * \param[in] cloud_src the source point cloud dataset
166  * \param[in] cloud_tgt the target point cloud dataset
167  * \param[out] transformation_matrix the resultant transformation matrix
168  *
169  * \return the score or confidence measure for the given
170  * transformation_matrix with respect to the input data
171  */
172  double
174  const PointCloudTargetConstPtr& cloud_tgt,
175  const Matrix4& transformation_matrix) const;
176 
177  /** \brief Comparator function for deciding which score is better after running the
178  * validation on multiple transforms.
179  *
180  * \param[in] score1 the first value
181  * \param[in] score2 the second value
182  *
183  * \return true if score1 is better than score2
184  */
185  virtual bool
186  operator()(const double& score1, const double& score2) const
187  {
188  return (score1 < score2);
189  }
190 
191  /** \brief Check if the score is valid for a specific transformation.
192  *
193  * \param[in] cloud_src the source point cloud dataset
194  * \param[in] cloud_tgt the target point cloud dataset
195  * \param[out] transformation_matrix the transformation matrix
196  *
197  * \return true if the transformation is valid, false otherwise.
198  */
199  virtual bool
201  const PointCloudTargetConstPtr& cloud_tgt,
202  const Matrix4& transformation_matrix) const
203  {
204  if (std::isnan(threshold_)) {
205  PCL_ERROR("[pcl::TransformationValidationEuclidean::isValid] Threshold not set! "
206  "Please use setThreshold () before continuing.\n");
207  return (false);
208  }
209 
210  return (validateTransformation(cloud_src, cloud_tgt, transformation_matrix) <
211  threshold_);
212  }
213 
214 protected:
215  /** \brief The maximum allowable distance between a point and its correspondence in
216  * the target in order for a correspondence to be considered \a valid. Default:
217  * double::max.
218  */
219  double max_range_;
220 
221  /** \brief The threshold for which a specific transformation is valid.
222  * Set to NaN by default, as we must require the user to set it.
223  */
224  double threshold_;
225 
226  /** \brief A pointer to the spatial search object. */
228 
229  /** \brief A flag which, if set, means the tree operating on the target cloud
230  * will never be recomputed*/
231  bool force_no_recompute_{false};
232 
233  /** \brief Internal point representation uses only 3D coordinates for L2 */
234  class MyPointRepresentation : public pcl::PointRepresentation<PointTarget> {
237 
238  public:
239  using Ptr = shared_ptr<MyPointRepresentation>;
240  using ConstPtr = shared_ptr<const MyPointRepresentation>;
241 
243  {
244  nr_dimensions_ = 3;
245  trivial_ = true;
246  }
247 
248  /** \brief Empty destructor */
249  virtual ~MyPointRepresentation() = default;
250 
251  virtual void
252  copyToFloatArray(const PointTarget& p, float* out) const
253  {
254  out[0] = p.x;
255  out[1] = p.y;
256  out[2] = p.z;
257  }
258  };
259 
260 public:
262 };
263 } // namespace registration
264 } // namespace pcl
265 
266 #include <pcl/registration/impl/transformation_validation_euclidean.hpp>
PointRepresentation provides a set of methods for converting a point structs/object into an n-dimensi...
int nr_dimensions_
The number of dimensions in this point's vector (i.e.
bool trivial_
Indicates whether this point representation is trivial.
virtual void copyToFloatArray(const PointTarget &p, float *out) const
Copy point data from input point to a float array.
TransformationValidationEuclidean computes an L2SQR norm between a source and target dataset.
void setThreshold(double threshold)
Set a threshold for which a specific transformation is considered valid.
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 bool operator()(const double &score1, const double &score2) const
Comparator function for deciding which score is better after running the validation on multiple trans...
bool force_no_recompute_
A flag which, if set, means the tree operating on the target cloud will never be recomputed.
shared_ptr< const TransformationValidation< PointSource, PointTarget, Scalar > > ConstPtr
double max_range_
The maximum allowable distance between a point and its correspondence in the target in order for a co...
double threshold_
The threshold for which a specific transformation is valid.
typename TransformationValidation< PointSource, PointTarget, Scalar >::Matrix4 Matrix4
typename TransformationValidation< PointSource, PointTarget >::PointCloudTargetConstPtr PointCloudTargetConstPtr
double validateTransformation(const PointCloudSourceConstPtr &cloud_src, const PointCloudTargetConstPtr &cloud_tgt, const Matrix4 &transformation_matrix) const
Validate the given transformation with respect to the input cloud data, and return a score.
void setMaxRange(double max_range)
Set the maximum allowable distance between a point and its correspondence in the target in order for ...
double getMaxRange()
Get the maximum allowable distance between a point and its correspondence, as set by the user.
typename TransformationValidation< PointSource, PointTarget >::PointCloudSourceConstPtr PointCloudSourceConstPtr
double getThreshold()
Get the threshold for which a specific transformation is valid.
shared_ptr< TransformationValidation< PointSource, PointTarget, Scalar > > Ptr
virtual bool isValid(const PointCloudSourceConstPtr &cloud_src, const PointCloudTargetConstPtr &cloud_tgt, const Matrix4 &transformation_matrix) const
Check if the score is valid for a specific transformation.
typename KdTree::PointRepresentationConstPtr PointRepresentationConstPtr
TransformationValidation represents the base class for methods that validate the correctness of a tra...
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
#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.
Defines all the PCL and non-PCL macros used.