IterativeClosestPoint provides a base implementation of the Iterative Closest Point algorithm. The transformation is estimated based on Singular Value Decomposition (SVD). More...

#include <icp.h>

Inheritance diagram for pcl::IterativeClosestPoint< PointSource, PointTarget, Scalar >:

[legend]

List of all members.

Public Types
typedef boost::shared_ptr < const IterativeClosestPoint < PointSource, PointTarget, Scalar > >	ConstPtr
typedef Registration < PointSource, PointTarget, Scalar >::Matrix4	Matrix4
typedef Registration < PointSource, PointTarget, Scalar >::PointCloudSource	PointCloudSource
typedef PointCloudSource::ConstPtr	PointCloudSourceConstPtr
typedef PointCloudSource::Ptr	PointCloudSourcePtr
typedef Registration < PointSource, PointTarget, Scalar >::PointCloudTarget	PointCloudTarget
typedef PointCloudTarget::ConstPtr	PointCloudTargetConstPtr
typedef PointCloudTarget::Ptr	PointCloudTargetPtr
typedef PointIndices::ConstPtr	PointIndicesConstPtr
typedef PointIndices::Ptr	PointIndicesPtr
typedef boost::shared_ptr < IterativeClosestPoint < PointSource, PointTarget, Scalar > >	Ptr
Public Member Functions
pcl::registration::DefaultConvergenceCriteria < Scalar >::Ptr	getConvergeCriteria ()
	Returns a pointer to the DefaultConvergenceCriteria used by the IterativeClosestPoint class. This allows to check the convergence state after the align() method as well as to configure DefaultConvergenceCriteria's parameters not available through the ICP API before the align() method is called. Please note that the align method sets max_iterations_, euclidean_fitness_epsilon_ and transformation_epsilon_ and therefore overrides the default / set values of the DefaultConvergenceCriteria instance.
bool	getUseReciprocalCorrespondences () const
	Obtain whether reciprocal correspondence are used or not.
	IterativeClosestPoint ()
	Empty constructor.
virtual 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 void	setInputTarget (const PointCloudTargetConstPtr &cloud)
	Provide a pointer to the input target (e.g., the point cloud that we want to align to the target)
void	setUseReciprocalCorrespondences (bool use_reciprocal_correspondence)
	Set whether to use reciprocal correspondence or not.
virtual	~IterativeClosestPoint ()
	Empty destructor.
Public Attributes
pcl::registration::DefaultConvergenceCriteria < Scalar >::Ptr	convergence_criteria_
Protected Member Functions
virtual void	computeTransformation (PointCloudSource &output, const Matrix4 &guess)
	Rigid transformation computation method with initial guess.
virtual void	transformCloud (const PointCloudSource &input, PointCloudSource &output, const Matrix4 &transform)
	Apply a rigid transform to a given dataset. Here we check whether whether the dataset has surface normals in addition to XYZ, and rotate normals as well.
Protected Attributes
size_t	nx_idx_offset_
	Normal fields offset.
size_t	ny_idx_offset_
size_t	nz_idx_offset_
bool	source_has_normals_
	Internal check whether source dataset has normals or not.
bool	target_has_normals_
	Internal check whether target dataset has normals or not.
bool	use_reciprocal_correspondence_
	The correspondence type used for correspondence estimation.
size_t	x_idx_offset_
	XYZ fields offset.
size_t	y_idx_offset_
size_t	z_idx_offset_

Detailed Description

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

IterativeClosestPoint provides a base implementation of the Iterative Closest Point algorithm. The transformation is estimated based on Singular Value Decomposition (SVD).

The algorithm has several termination criteria:

Number of iterations has reached the maximum user imposed number of iterations (via setMaximumIterations)
The epsilon (difference) between the previous transformation and the current estimated transformation is smaller than an user imposed value (via setTransformationEpsilon)
The sum of Euclidean squared errors is smaller than a user defined threshold (via setEuclideanFitnessEpsilon)

Usage example:

 IterativeClosestPoint<PointXYZ, PointXYZ> icp;
 // Set the input source and target
 icp.setInputCloud (cloud_source);
 icp.setInputTarget (cloud_target);

 // Set the max correspondence distance to 5cm (e.g., correspondences with higher distances will be ignored)
 icp.setMaxCorrespondenceDistance (0.05);
 // Set the maximum number of iterations (criterion 1)
 icp.setMaximumIterations (50);
 // Set the transformation epsilon (criterion 2)
 icp.setTransformationEpsilon (1e-8);
 // Set the euclidean distance difference epsilon (criterion 3)
 icp.setEuclideanFitnessEpsilon (1);

 // Perform the alignment
 icp.align (cloud_source_registered);

 // Obtain the transformation that aligned cloud_source to cloud_source_registered
 Eigen::Matrix4f transformation = icp.getFinalTransformation ();

Author:: Radu B. Rusu, Michael Dixon

Definition at line 94 of file registration/include/pcl/registration/icp.h.

Member Typedef Documentation

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

typedef boost::shared_ptr<const IterativeClosestPoint<PointSource, PointTarget, Scalar> > pcl::IterativeClosestPoint< PointSource, PointTarget, Scalar >::ConstPtr

Reimplemented from pcl::Registration< PointSource, PointTarget, Scalar >.

Reimplemented in pcl::IterativeClosestPointWithNormals< PointSource, PointTarget, Scalar >, pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >, and pcl::IterativeClosestPointNonLinear< PointSource, PointTarget, Scalar >.

Definition at line 109 of file registration/include/pcl/registration/icp.h.

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

typedef Registration<PointSource, PointTarget, Scalar>::Matrix4 pcl::IterativeClosestPoint< PointSource, PointTarget, Scalar >::Matrix4

Reimplemented from pcl::Registration< PointSource, PointTarget, Scalar >.

Reimplemented in pcl::IterativeClosestPointWithNormals< PointSource, PointTarget, Scalar >, and pcl::IterativeClosestPointNonLinear< PointSource, PointTarget, Scalar >.

Definition at line 135 of file registration/include/pcl/registration/icp.h.

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

typedef Registration<PointSource, PointTarget, Scalar>::PointCloudSource pcl::IterativeClosestPoint< PointSource, PointTarget, Scalar >::PointCloudSource

Reimplemented from pcl::Registration< PointSource, PointTarget, Scalar >.

Reimplemented in pcl::IterativeClosestPointWithNormals< PointSource, PointTarget, Scalar >, and pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >.

Definition at line 97 of file registration/include/pcl/registration/icp.h.

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

typedef PointCloudSource::ConstPtr pcl::IterativeClosestPoint< PointSource, PointTarget, Scalar >::PointCloudSourceConstPtr

Reimplemented from pcl::Registration< PointSource, PointTarget, Scalar >.

Reimplemented in pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >.

Definition at line 99 of file registration/include/pcl/registration/icp.h.

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

typedef PointCloudSource::Ptr pcl::IterativeClosestPoint< PointSource, PointTarget, Scalar >::PointCloudSourcePtr

Reimplemented from pcl::Registration< PointSource, PointTarget, Scalar >.

Reimplemented in pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >.

Definition at line 98 of file registration/include/pcl/registration/icp.h.

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

typedef Registration<PointSource, PointTarget, Scalar>::PointCloudTarget pcl::IterativeClosestPoint< PointSource, PointTarget, Scalar >::PointCloudTarget

Reimplemented from pcl::Registration< PointSource, PointTarget, Scalar >.

Reimplemented in pcl::IterativeClosestPointWithNormals< PointSource, PointTarget, Scalar >, and pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >.

Definition at line 101 of file registration/include/pcl/registration/icp.h.

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

typedef PointCloudTarget::ConstPtr pcl::IterativeClosestPoint< PointSource, PointTarget, Scalar >::PointCloudTargetConstPtr

Reimplemented from pcl::Registration< PointSource, PointTarget, Scalar >.

Reimplemented in pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >.

Definition at line 103 of file registration/include/pcl/registration/icp.h.

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

typedef PointCloudTarget::Ptr pcl::IterativeClosestPoint< PointSource, PointTarget, Scalar >::PointCloudTargetPtr

Reimplemented from pcl::Registration< PointSource, PointTarget, Scalar >.

Reimplemented in pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >.

Definition at line 102 of file registration/include/pcl/registration/icp.h.

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

typedef PointIndices::ConstPtr pcl::IterativeClosestPoint< PointSource, PointTarget, Scalar >::PointIndicesConstPtr

Reimplemented from pcl::PCLBase< PointSource >.

Reimplemented in pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >.

Definition at line 106 of file registration/include/pcl/registration/icp.h.

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

typedef PointIndices::Ptr pcl::IterativeClosestPoint< PointSource, PointTarget, Scalar >::PointIndicesPtr

Reimplemented from pcl::PCLBase< PointSource >.

Reimplemented in pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >.

Definition at line 105 of file registration/include/pcl/registration/icp.h.

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

typedef boost::shared_ptr<IterativeClosestPoint<PointSource, PointTarget, Scalar> > pcl::IterativeClosestPoint< PointSource, PointTarget, Scalar >::Ptr

Reimplemented from pcl::Registration< PointSource, PointTarget, Scalar >.

Reimplemented in pcl::IterativeClosestPointWithNormals< PointSource, PointTarget, Scalar >, pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >, and pcl::IterativeClosestPointNonLinear< PointSource, PointTarget, Scalar >.

Definition at line 108 of file registration/include/pcl/registration/icp.h.

Constructor & Destructor Documentation

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

pcl::IterativeClosestPoint< PointSource, PointTarget, Scalar >::IterativeClosestPoint ( ) [inline]

Empty constructor.

Definition at line 138 of file registration/include/pcl/registration/icp.h.

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

virtual pcl::IterativeClosestPoint< PointSource, PointTarget, Scalar >::~IterativeClosestPoint ( ) [inline, virtual]

Empty destructor.

Definition at line 156 of file registration/include/pcl/registration/icp.h.

Member Function Documentation

template<typename PointSource , typename PointTarget , typename Scalar >

void pcl::IterativeClosestPoint< PointSource, PointTarget, Scalar >::computeTransformation	(	PointCloudSource &	output,
		const Matrix4 &	guess
	)		`[protected, virtual]`

Rigid transformation computation method with initial guess.

Parameters:

output	the transformed input point cloud dataset using the rigid transformation found
guess	the initial guess of the transformation to compute

Implements pcl::Registration< PointSource, PointTarget, Scalar >.

Definition at line 119 of file icp.hpp.

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

pcl::registration::DefaultConvergenceCriteria<Scalar>::Ptr pcl::IterativeClosestPoint< PointSource, PointTarget, Scalar >::getConvergeCriteria ( ) [inline]

Returns a pointer to the DefaultConvergenceCriteria used by the IterativeClosestPoint class. This allows to check the convergence state after the align() method as well as to configure DefaultConvergenceCriteria's parameters not available through the ICP API before the align() method is called. Please note that the align method sets max_iterations_, euclidean_fitness_epsilon_ and transformation_epsilon_ and therefore overrides the default / set values of the DefaultConvergenceCriteria instance.

Parameters:

[out] Pointer to the IterativeClosestPoint's DefaultConvergenceCriteria.

Definition at line 167 of file registration/include/pcl/registration/icp.h.

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

bool pcl::IterativeClosestPoint< PointSource, PointTarget, Scalar >::getUseReciprocalCorrespondences ( ) const [inline]

Obtain whether reciprocal correspondence are used or not.

Definition at line 241 of file registration/include/pcl/registration/icp.h.

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

virtual void pcl::IterativeClosestPoint< PointSource, PointTarget, Scalar >::setInputSource ( const PointCloudSourceConstPtr & cloud ) [inline, virtual]

Provide a pointer to the input source (e.g., the point cloud that we want to align to the target)

Parameters:

[in] cloud the input point cloud source

Definition at line 178 of file registration/include/pcl/registration/icp.h.

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

virtual void pcl::IterativeClosestPoint< PointSource, PointTarget, Scalar >::setInputTarget ( const PointCloudTargetConstPtr & cloud ) [inline, virtual]

Provide a pointer to the input target (e.g., the point cloud that we want to align to the target)

Parameters:

[in] cloud the input point cloud target

Definition at line 213 of file registration/include/pcl/registration/icp.h.

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

void pcl::IterativeClosestPoint< PointSource, PointTarget, Scalar >::setUseReciprocalCorrespondences ( bool use_reciprocal_correspondence ) [inline]

Set whether to use reciprocal correspondence or not.

Parameters:

[in] use_reciprocal_correspondence whether to use reciprocal correspondence or not

Definition at line 234 of file registration/include/pcl/registration/icp.h.

template<typename PointSource , typename PointTarget , typename Scalar >

void pcl::IterativeClosestPoint< PointSource, PointTarget, Scalar >::transformCloud	(	const PointCloudSource &	input,
		PointCloudSource &	output,
		const Matrix4 &	transform
	)		`[protected, virtual]`

Apply a rigid transform to a given dataset. Here we check whether whether the dataset has surface normals in addition to XYZ, and rotate normals as well.

Parameters:

[in]	input	the input point cloud
[out]	output	the resultant output point cloud
[in]	transform	a 4x4 rigid transformation

Note:: Can be used with cloud_in equal to cloud_out

Reimplemented in pcl::IterativeClosestPointWithNormals< PointSource, PointTarget, Scalar >.

Definition at line 49 of file icp.hpp.

Member Data Documentation

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

pcl::registration::DefaultConvergenceCriteria<Scalar>::Ptr pcl::IterativeClosestPoint< PointSource, PointTarget, Scalar >::convergence_criteria_

Definition at line 134 of file registration/include/pcl/registration/icp.h.

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

size_t pcl::IterativeClosestPoint< PointSource, PointTarget, Scalar >::nx_idx_offset_ [protected]

Normal fields offset.

Definition at line 271 of file registration/include/pcl/registration/icp.h.

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

size_t pcl::IterativeClosestPoint< PointSource, PointTarget, Scalar >::ny_idx_offset_ [protected]

Definition at line 271 of file registration/include/pcl/registration/icp.h.

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

size_t pcl::IterativeClosestPoint< PointSource, PointTarget, Scalar >::nz_idx_offset_ [protected]

Definition at line 271 of file registration/include/pcl/registration/icp.h.

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

bool pcl::IterativeClosestPoint< PointSource, PointTarget, Scalar >::source_has_normals_ [protected]

Internal check whether source dataset has normals or not.

Definition at line 277 of file registration/include/pcl/registration/icp.h.

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

bool pcl::IterativeClosestPoint< PointSource, PointTarget, Scalar >::target_has_normals_ [protected]

Internal check whether target dataset has normals or not.

Definition at line 279 of file registration/include/pcl/registration/icp.h.

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

bool pcl::IterativeClosestPoint< PointSource, PointTarget, Scalar >::use_reciprocal_correspondence_ [protected]

The correspondence type used for correspondence estimation.

Definition at line 274 of file registration/include/pcl/registration/icp.h.

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

size_t pcl::IterativeClosestPoint< PointSource, PointTarget, Scalar >::x_idx_offset_ [protected]

XYZ fields offset.

Definition at line 268 of file registration/include/pcl/registration/icp.h.

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

size_t pcl::IterativeClosestPoint< PointSource, PointTarget, Scalar >::y_idx_offset_ [protected]

Definition at line 268 of file registration/include/pcl/registration/icp.h.

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

size_t pcl::IterativeClosestPoint< PointSource, PointTarget, Scalar >::z_idx_offset_ [protected]

Definition at line 268 of file registration/include/pcl/registration/icp.h.

The documentation for this class was generated from the following files:

Public Types

Public Member Functions

Public Attributes

Protected Member Functions

Protected Attributes

Detailed Description

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

Member Typedef Documentation

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation

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