TransformationValidationEuclidean computes an L2SQR norm between a source and target dataset. More...

#include <pcl/registration/transformation_validation_euclidean.h>

Collaboration diagram for pcl::registration::TransformationValidationEuclidean< PointSource, PointTarget, Scalar >:

Classes
class	MyPointRepresentation
	Internal point representation uses only 3D coordinates for L2. More...

Public Types
using	Matrix4 = typename TransformationValidation< PointSource, PointTarget, Scalar >::Matrix4

using	Ptr = shared_ptr< TransformationValidation< PointSource, PointTarget, Scalar > >

using	ConstPtr = shared_ptr< const TransformationValidation< PointSource, PointTarget, Scalar > >

using	KdTree = pcl::search::KdTree< PointTarget >

using	KdTreePtr = typename KdTree::Ptr

using	PointRepresentationConstPtr = typename KdTree::PointRepresentationConstPtr

using	PointCloudSourceConstPtr = typename TransformationValidation< PointSource, PointTarget >::PointCloudSourceConstPtr

using	PointCloudTargetConstPtr = typename TransformationValidation< PointSource, PointTarget >::PointCloudTargetConstPtr

Public Member Functions
	TransformationValidationEuclidean ()
	Constructor. More...

virtual	~TransformationValidationEuclidean ()=default

void	setMaxRange (double max_range)
	Set the maximum allowable distance between a point and its correspondence in the target in order for a correspondence to be considered valid. More...

double	getMaxRange ()
	Get the maximum allowable distance between a point and its correspondence, as set by the user. More...

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. More...

void	setThreshold (double threshold)
	Set a threshold for which a specific transformation is considered valid. More...

double	getThreshold ()
	Get the threshold for which a specific transformation is valid. More...

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. More...

virtual bool	operator() (const double &score1, const double &score2) const
	Comparator function for deciding which score is better after running the validation on multiple transforms. More...

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. More...

Protected Attributes
double	max_range_
	The maximum allowable distance between a point and its correspondence in the target in order for a correspondence to be considered valid. More...

double	threshold_
	The threshold for which a specific transformation is valid. More...

KdTreePtr	tree_
	A pointer to the spatial search object. More...

bool	force_no_recompute_ {false}
	A flag which, if set, means the tree operating on the target cloud will never be recomputed. More...

Detailed Description

template<typename PointSource, typename PointTarget, typename Scalar = float>
class pcl::registration::TransformationValidationEuclidean< PointSource, PointTarget, Scalar >

TransformationValidationEuclidean computes an L2SQR norm between a source and target dataset.

To prevent points with bad correspondences to contribute to the overall score, the class also accepts a maximum_range parameter given via setMaxRange that is used as a cutoff value for nearest neighbor distance comparisons.

The output score is normalized with respect to the number of valid correspondences found.

Usage example:

pcl::TransformationValidationEuclidean<pcl::PointXYZ, pcl::PointXYZ> tve;
tve.setMaxRange (0.01);  // 1cm
double score = tve.validateTransformation (source, target, transformation);

Note: The class is templated on the source and target point types as well as on the output scalar of the transformation matrix (i.e., float or double). Default: float.

Author: Radu B. Rusu

Definition at line 75 of file transformation_validation_euclidean.h.

Member Typedef Documentation

◆ ConstPtr

template<typename PointSource , typename PointTarget , typename Scalar = float>

using pcl::registration::TransformationValidationEuclidean< PointSource, PointTarget, Scalar >::ConstPtr = shared_ptr<const TransformationValidation<PointSource, PointTarget, Scalar> >

Definition at line 81 of file transformation_validation_euclidean.h.

◆ KdTree

template<typename PointSource , typename PointTarget , typename Scalar = float>

using pcl::registration::TransformationValidationEuclidean< PointSource, PointTarget, Scalar >::KdTree = pcl::search::KdTree<PointTarget>

Definition at line 84 of file transformation_validation_euclidean.h.

◆ KdTreePtr

template<typename PointSource , typename PointTarget , typename Scalar = float>

using pcl::registration::TransformationValidationEuclidean< PointSource, PointTarget, Scalar >::KdTreePtr = typename KdTree::Ptr

Definition at line 85 of file transformation_validation_euclidean.h.

◆ Matrix4

template<typename PointSource , typename PointTarget , typename Scalar = float>

using pcl::registration::TransformationValidationEuclidean< PointSource, PointTarget, Scalar >::Matrix4 = typename TransformationValidation<PointSource, PointTarget, Scalar>::Matrix4

Definition at line 77 of file transformation_validation_euclidean.h.

◆ PointCloudSourceConstPtr

template<typename PointSource , typename PointTarget , typename Scalar = float>

using pcl::registration::TransformationValidationEuclidean< PointSource, PointTarget, Scalar >::PointCloudSourceConstPtr = typename TransformationValidation<PointSource, PointTarget>::PointCloudSourceConstPtr

Definition at line 89 of file transformation_validation_euclidean.h.

◆ PointCloudTargetConstPtr

template<typename PointSource , typename PointTarget , typename Scalar = float>

using pcl::registration::TransformationValidationEuclidean< PointSource, PointTarget, Scalar >::PointCloudTargetConstPtr = typename TransformationValidation<PointSource, PointTarget>::PointCloudTargetConstPtr

Definition at line 92 of file transformation_validation_euclidean.h.

◆ PointRepresentationConstPtr

template<typename PointSource , typename PointTarget , typename Scalar = float>

using pcl::registration::TransformationValidationEuclidean< PointSource, PointTarget, Scalar >::PointRepresentationConstPtr = typename KdTree::PointRepresentationConstPtr

Definition at line 87 of file transformation_validation_euclidean.h.

◆ Ptr

template<typename PointSource , typename PointTarget , typename Scalar = float>

using pcl::registration::TransformationValidationEuclidean< PointSource, PointTarget, Scalar >::Ptr = shared_ptr<TransformationValidation<PointSource, PointTarget, Scalar> >

Definition at line 80 of file transformation_validation_euclidean.h.

Constructor & Destructor Documentation

◆ TransformationValidationEuclidean()

template<typename PointSource , typename PointTarget , typename Scalar = float>

pcl::registration::TransformationValidationEuclidean< PointSource, PointTarget, Scalar >::TransformationValidationEuclidean ( )

inline

Constructor.

Sets the max_range parameter to double::max, threshold_ to NaN and initializes the internal search tree to a FLANN kd-tree.

Definition at line 100 of file transformation_validation_euclidean.h.

◆ ~TransformationValidationEuclidean()

template<typename PointSource , typename PointTarget , typename Scalar = float>

virtual pcl::registration::TransformationValidationEuclidean< PointSource, PointTarget, Scalar >::~TransformationValidationEuclidean ( )

virtualdefault

Member Function Documentation

◆ getMaxRange()

template<typename PointSource , typename PointTarget , typename Scalar = float>

double pcl::registration::TransformationValidationEuclidean< PointSource, PointTarget, Scalar >::getMaxRange ( )

inline

Get the maximum allowable distance between a point and its correspondence, as set by the user.

Definition at line 122 of file transformation_validation_euclidean.h.

References pcl::registration::TransformationValidationEuclidean< PointSource, PointTarget, Scalar >::max_range_.

◆ getThreshold()

template<typename PointSource , typename PointTarget , typename Scalar = float>

double pcl::registration::TransformationValidationEuclidean< PointSource, PointTarget, Scalar >::getThreshold ( )

inline

Get the threshold for which a specific transformation is valid.

Definition at line 157 of file transformation_validation_euclidean.h.

References pcl::registration::TransformationValidationEuclidean< PointSource, PointTarget, Scalar >::threshold_.

◆ isValid()

template<typename PointSource , typename PointTarget , typename Scalar = float>

virtual bool pcl::registration::TransformationValidationEuclidean< PointSource, PointTarget, Scalar >::isValid	(	const PointCloudSourceConstPtr &	cloud_src,
		const PointCloudTargetConstPtr &	cloud_tgt,
		const Matrix4 &	transformation_matrix
	)		const

inlinevirtual

Check if the score is valid for a specific transformation.

Parameters

[in]	cloud_src	the source point cloud dataset
[in]	cloud_tgt	the target point cloud dataset
[out]	transformation_matrix	the transformation matrix

Returns: true if the transformation is valid, false otherwise.

Definition at line 200 of file transformation_validation_euclidean.h.

References pcl::registration::TransformationValidationEuclidean< PointSource, PointTarget, Scalar >::threshold_, and pcl::registration::TransformationValidationEuclidean< PointSource, PointTarget, Scalar >::validateTransformation().

◆ operator()()

template<typename PointSource , typename PointTarget , typename Scalar = float>

virtual bool pcl::registration::TransformationValidationEuclidean< PointSource, PointTarget, Scalar >::operator()	(	const double &	score1,
		const double &	score2
	)		const

inlinevirtual

Comparator function for deciding which score is better after running the validation on multiple transforms.

Parameters

[in]	score1	the first value
[in]	score2	the second value

Returns: true if score1 is better than score2

Definition at line 186 of file transformation_validation_euclidean.h.

◆ setMaxRange()

template<typename PointSource , typename PointTarget , typename Scalar = float>

void pcl::registration::TransformationValidationEuclidean< PointSource, PointTarget, Scalar >::setMaxRange ( double max_range )

inline

Set the maximum allowable distance between a point and its correspondence in the target in order for a correspondence to be considered valid.

Default: double::max.

Parameters

[in] max_range the new maximum allowable distance

Definition at line 113 of file transformation_validation_euclidean.h.

References pcl::registration::TransformationValidationEuclidean< PointSource, PointTarget, Scalar >::max_range_.

◆ setSearchMethodTarget()

template<typename PointSource , typename PointTarget , typename Scalar = float>

void pcl::registration::TransformationValidationEuclidean< PointSource, PointTarget, Scalar >::setSearchMethodTarget	(	const KdTreePtr &	tree,
		bool	force_no_recompute = `false`
	)

inline

Provide a pointer to the search object used to find correspondences in the target cloud.

Parameters

[in]	tree	a pointer to the spatial search object.
[in]	force_no_recompute	If set to true, this tree will NEVER be recomputed, regardless of calls to setInputTarget. Only use if you are confident that the tree will be set correctly.

Definition at line 135 of file transformation_validation_euclidean.h.

References pcl::registration::TransformationValidationEuclidean< PointSource, PointTarget, Scalar >::force_no_recompute_, and pcl::registration::TransformationValidationEuclidean< PointSource, PointTarget, Scalar >::tree_.

◆ setThreshold()

template<typename PointSource , typename PointTarget , typename Scalar = float>

void pcl::registration::TransformationValidationEuclidean< PointSource, PointTarget, Scalar >::setThreshold ( double threshold )

inline

Set a threshold for which a specific transformation is considered valid.

Note: Since we're using MSE (Mean Squared Error) as a metric, the threshold represents the mean Euclidean distance threshold over all nearest neighbors up to max_range.

Parameters

[in] threshold the threshold for which a transformation is vali

Definition at line 150 of file transformation_validation_euclidean.h.

References pcl::registration::TransformationValidationEuclidean< PointSource, PointTarget, Scalar >::threshold_.

◆ validateTransformation()

template<typename PointSource , typename PointTarget , typename Scalar >

double pcl::registration::TransformationValidationEuclidean< PointSource, PointTarget, Scalar >::validateTransformation	(	const PointCloudSourceConstPtr &	cloud_src,
		const PointCloudTargetConstPtr &	cloud_tgt,
		const Matrix4 &	transformation_matrix
	)		const