pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget > Class Template Reference
[Module registration]

GeneralizedIterativeClosestPoint is an ICP variant that implements the generalized iterative closest point algorithm as described by Alex Segal et al. More...

#include <pcl/registration/gicp.h>

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List of all members.

Classes

struct  OptimizationFunctorWithIndices
 optimization functor structure More...

Public Types

typedef pcl::PointCloud
< PointSource > 		PointCloudSource
typedef PointCloudSource::Ptr PointCloudSourcePtr
typedef PointCloudSource::ConstPtr PointCloudSourceConstPtr
typedef pcl::PointCloud
< PointTarget > 		PointCloudTarget
typedef PointCloudTarget::Ptr PointCloudTargetPtr
typedef PointCloudTarget::ConstPtr PointCloudTargetConstPtr
typedef PointIndices::Ptr PointIndicesPtr
typedef PointIndices::ConstPtr PointIndicesConstPtr
typedef Registration
< PointSource, PointTarget >
::KdTree 		InputKdTree
typedef Registration
< PointSource, PointTarget >
::KdTreePtr 		InputKdTreePtr
typedef boost::shared_ptr
< GeneralizedIterativeClosestPoint
< PointSource, PointTarget > > 		Ptr
typedef boost::shared_ptr
< const
GeneralizedIterativeClosestPoint
< PointSource, PointTarget > > 		ConstPtr
typedef Eigen::Matrix< double, 6, 1 > Vector6d

Public Member Functions

 GeneralizedIterativeClosestPoint ()
 Empty constructor.
 PCL_DEPRECATED (void setInputCloud(const PointCloudSourceConstPtr &cloud),"[pcl::registration::GeneralizedIterativeClosestPoint::setInputCloud] setInputCloud is deprecated. Please use setInputSource instead.")
 Provide a pointer to the input dataset.
void setInputSource (const PointCloudSourceConstPtr &cloud)
 Provide a pointer to the input dataset.
void setInputTarget (const PointCloudTargetConstPtr &target)
 Provide a pointer to the input target (e.g., the point cloud that we want to align the input source to).
void estimateRigidTransformationBFGS (const PointCloudSource &cloud_src, const std::vector< int > &indices_src, const PointCloudTarget &cloud_tgt, const std::vector< int > &indices_tgt, Eigen::Matrix4f &transformation_matrix)
 Estimate a rigid rotation transformation between a source and a target point cloud using an iterative non-linear Levenberg-Marquardt approach.
const Eigen::Matrix3d & mahalanobis (size_t index) const
void computeRDerivative (const Vector6d &x, const Eigen::Matrix3d &R, Vector6d &g) const
 Computes rotation matrix derivative.
void setRotationEpsilon (double epsilon)
 Set the rotation epsilon (maximum allowable difference between two consecutive rotations) in order for an optimization to be considered as having converged to the final solution.
double getRotationEpsilon ()
 Get the rotation epsilon (maximum allowable difference between two consecutive rotations) as set by the user.
void setCorrespondenceRandomness (int k)
 Set the number of neighbors used when selecting a point neighbourhood to compute covariances.
int getCorrespondenceRandomness ()
 Get the number of neighbors used when computing covariances as set by the user.
void setMaximumOptimizerIterations (int max)
 set maximum number of iterations at the optimization step
int getMaximumOptimizerIterations ()

Protected Member Functions

template<typename PointT >
void computeCovariances (typename pcl::PointCloud< PointT >::ConstPtr cloud, const typename pcl::search::KdTree< PointT >::Ptr tree, std::vector< Eigen::Matrix3d > &cloud_covariances)
 compute points covariances matrices according to the K nearest neighbors.
double matricesInnerProd (const Eigen::MatrixXd &mat1, const Eigen::MatrixXd &mat2) const
void computeTransformation (PointCloudSource &output, const Eigen::Matrix4f &guess)
 Rigid transformation computation method with initial guess.
bool searchForNeighbors (const PointSource &query, std::vector< int > &index, std::vector< float > &distance)
 Search for the closest nearest neighbor of a given point.
void applyState (Eigen::Matrix4f &t, const Vector6d &x) const
 compute transformation matrix from transformation matrix

Protected Attributes

int k_correspondences_
 The number of neighbors used for covariances computation.
double gicp_epsilon_
 The epsilon constant for gicp paper; this is NOT the convergence tolerence default: 0.001.
double rotation_epsilon_
 The epsilon constant for rotation error.
Eigen::Matrix4f base_transformation_
 base transformation
const PointCloudSource * tmp_src_
 Temporary pointer to the source dataset.
const PointCloudTarget * tmp_tgt_
 Temporary pointer to the target dataset.
const std::vector< int > * tmp_idx_src_
 Temporary pointer to the source dataset indices.
const std::vector< int > * tmp_idx_tgt_
 Temporary pointer to the target dataset indices.
std::vector< Eigen::Matrix3d > input_covariances_
 Input cloud points covariances.
std::vector< Eigen::Matrix3d > target_covariances_
 Target cloud points covariances.
std::vector< Eigen::Matrix3d > mahalanobis_
 Mahalanobis matrices holder.
int max_inner_iterations_
 maximum number of optimizations
boost::function< void(const
pcl::PointCloud< PointSource >
&cloud_src, const std::vector
< int > &src_indices, const
pcl::PointCloud< PointTarget >
&cloud_tgt, const std::vector
< int > &tgt_indices,
Eigen::Matrix4f
&transformation_matrix)> 		rigid_transformation_estimation_

Detailed Description

template<typename PointSource, typename PointTarget>
class pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >

GeneralizedIterativeClosestPoint is an ICP variant that implements the generalized iterative closest point algorithm as described by Alex Segal et al.

in http://www.stanford.edu/~avsegal/resources/papers/Generalized_ICP.pdf The approach is based on using anistropic cost functions to optimize the alignment after closest point assignments have been made. The original code uses GSL and ANN while in ours we use an eigen mapped BFGS and FLANN.

Author:
Nizar Sallem

Definition at line 60 of file gicp.h.

Member Typedef Documentation

template<typename PointSource, typename PointTarget>
typedef boost::shared_ptr< const GeneralizedIterativeClosestPoint<PointSource, PointTarget> > pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::ConstPtr

Reimplemented from pcl::IterativeClosestPoint< PointSource, PointTarget >.

Definition at line 97 of file gicp.h.

template<typename PointSource, typename PointTarget>
typedef Registration<PointSource, PointTarget>::KdTree pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::InputKdTree

Definition at line 93 of file gicp.h.

template<typename PointSource, typename PointTarget>
typedef Registration<PointSource, PointTarget>::KdTreePtr pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::InputKdTreePtr

Definition at line 94 of file gicp.h.

template<typename PointSource, typename PointTarget>
typedef pcl::PointCloud<PointSource> pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::PointCloudSource

Reimplemented from pcl::IterativeClosestPoint< PointSource, PointTarget >.

Definition at line 82 of file gicp.h.

template<typename PointSource, typename PointTarget>
typedef PointCloudSource::ConstPtr pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::PointCloudSourceConstPtr

Reimplemented from pcl::IterativeClosestPoint< PointSource, PointTarget >.

Definition at line 84 of file gicp.h.

template<typename PointSource, typename PointTarget>
typedef PointCloudSource::Ptr pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::PointCloudSourcePtr

Reimplemented from pcl::IterativeClosestPoint< PointSource, PointTarget >.

Definition at line 83 of file gicp.h.

template<typename PointSource, typename PointTarget>
typedef pcl::PointCloud<PointTarget> pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::PointCloudTarget

Reimplemented from pcl::IterativeClosestPoint< PointSource, PointTarget >.

Definition at line 86 of file gicp.h.

template<typename PointSource, typename PointTarget>
typedef PointCloudTarget::ConstPtr pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::PointCloudTargetConstPtr

Reimplemented from pcl::IterativeClosestPoint< PointSource, PointTarget >.

Definition at line 88 of file gicp.h.

template<typename PointSource, typename PointTarget>
typedef PointCloudTarget::Ptr pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::PointCloudTargetPtr

Reimplemented from pcl::IterativeClosestPoint< PointSource, PointTarget >.

Definition at line 87 of file gicp.h.

template<typename PointSource, typename PointTarget>
typedef PointIndices::ConstPtr pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::PointIndicesConstPtr

Reimplemented from pcl::IterativeClosestPoint< PointSource, PointTarget >.

Definition at line 91 of file gicp.h.

template<typename PointSource, typename PointTarget>
typedef PointIndices::Ptr pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::PointIndicesPtr

Reimplemented from pcl::IterativeClosestPoint< PointSource, PointTarget >.

Definition at line 90 of file gicp.h.

template<typename PointSource, typename PointTarget>
typedef boost::shared_ptr< GeneralizedIterativeClosestPoint<PointSource, PointTarget> > pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::Ptr

Reimplemented from pcl::IterativeClosestPoint< PointSource, PointTarget >.

Definition at line 96 of file gicp.h.

template<typename PointSource, typename PointTarget>
typedef Eigen::Matrix<double, 6, 1> pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::Vector6d

Definition at line 100 of file gicp.h.

Constructor & Destructor Documentation

template<typename PointSource, typename PointTarget>
pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::GeneralizedIterativeClosestPoint (  )  [inline]

Empty constructor.

Definition at line 103 of file gicp.h.

References pcl::Registration< PointSource, PointTarget, float >::corr_dist_threshold_, pcl::Registration< PointSource, PointTarget, float >::max_iterations_, pcl::Registration< PointSource, PointTarget, float >::min_number_correspondences_, pcl::Registration< PointSource, PointTarget, float >::reg_name_, pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::rigid_transformation_estimation_, and pcl::Registration< PointSource, PointTarget, float >::transformation_epsilon_.

Member Function Documentation

template<typename PointSource , typename PointTarget >
void pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::applyState ( Eigen::Matrix4f &  t,
const Vector6d &  x 
) const [inline, protected]

compute transformation matrix from transformation matrix

Definition at line 471 of file gicp.hpp.

Referenced by pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::OptimizationFunctorWithIndices::df(), pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::estimateRigidTransformationBFGS(), pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::OptimizationFunctorWithIndices::fdf(), and pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::OptimizationFunctorWithIndices::operator()().

template<typename PointSource , typename PointTarget >
template<typename PointT >
void pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::computeCovariances ( typename pcl::PointCloud< PointT >::ConstPtr  cloud,
const typename pcl::search::KdTree< PointT >::Ptr  tree,
std::vector< Eigen::Matrix3d > &  cloud_covariances 
) [inline, protected]

compute points covariances matrices according to the K nearest neighbors.

K is set via setCorrespondenceRandomness() methode.

Parameters:
cloud pointer to point cloud
tree KD tree performer for nearest neighbors search
Returns:
cloud_covariance covariances matrices for each point in the cloud

Definition at line 57 of file gicp.hpp.

References pcl::PointCloud< PointT >::begin(), pcl::PointCloud< PointT >::end(), pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::gicp_epsilon_, pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::k_correspondences_, pcl::search::KdTree< PointT >::nearestKSearch(), and pcl::PointCloud< PointT >::size().

template<typename PointSource , typename PointTarget >
void pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::computeRDerivative ( const Vector6d &  x,
const Eigen::Matrix3d &  R,
Vector6d &  g 
) const [inline]

Computes rotation matrix derivative.

rotation matrix is obtainded from rotation angles x[3], x[4] and x[5]

Returns:
d/d_rx, d/d_ry and d/d_rz respectively in g[3], g[4] and g[5] param x array representing 3D transformation param R rotation matrix param g gradient vector

Definition at line 135 of file gicp.hpp.

References pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::matricesInnerProd().

Referenced by pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::OptimizationFunctorWithIndices::df(), and pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::OptimizationFunctorWithIndices::fdf().

template<typename PointSource , typename PointTarget >
void pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::computeTransformation ( PointCloudSource &  output,
const Eigen::Matrix4f &  guess 
) [inline, protected]

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

Definition at line 352 of file gicp.hpp.

References pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::base_transformation_, pcl::Registration< PointSource, PointTarget, float >::converged_, pcl::Registration< PointSource, PointTarget, float >::corr_dist_threshold_, pcl::Registration< PointSource, PointTarget, float >::final_transformation_, pcl::Registration< PointSource, PointTarget, float >::getClassName(), pcl::PCLBase< PointSource >::indices_, pcl::Registration< PointSource, PointTarget, float >::initComputeReciprocal(), pcl::PCLBase< PointSource >::input_, pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::input_covariances_, pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::mahalanobis_, pcl::Registration< PointSource, PointTarget, float >::max_iterations_, pcl::Registration< PointSource, PointTarget, float >::nr_iterations_, pcl::Registration< PointSource, PointTarget, float >::previous_transformation_, pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::rigid_transformation_estimation_, pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::rotation_epsilon_, pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::searchForNeighbors(), pcl::Registration< PointSource, PointTarget, float >::target_, pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::target_covariances_, pcl::Registration< PointSource, PointTarget, float >::transformation_, pcl::Registration< PointSource, PointTarget, float >::transformation_epsilon_, pcl::Registration< PointSource, PointTarget, float >::tree_, pcl::Registration< PointSource, PointTarget, float >::tree_reciprocal_, and pcl::PCLException::what().

template<typename PointSource , typename PointTarget >
void pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::estimateRigidTransformationBFGS ( const PointCloudSource &  cloud_src,
const std::vector< int > &  indices_src,
const PointCloudTarget &  cloud_tgt,
const std::vector< int > &  indices_tgt,
Eigen::Matrix4f &  transformation_matrix 
) [inline]

Estimate a rigid rotation transformation between a source and a target point cloud using an iterative non-linear Levenberg-Marquardt approach.

Parameters:
[in] cloud_src the source point cloud dataset
[in] indices_src the vector of indices describing the points of interest in cloud_src
[in] cloud_tgt the target point cloud dataset
[in] indices_tgt the vector of indices describing the correspondences of the interst points from indices_src
[out] transformation_matrix the resultant transformation matrix

Definition at line 190 of file gicp.hpp.

References pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::applyState(), pcl::Registration< PointSource, PointTarget, float >::getClassName(), pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::max_inner_iterations_, BFGS< FunctorType >::minimizeInit(), BFGS< FunctorType >::minimizeOneStep(), BFGSSpace::NoProgress, BFGS< FunctorType >::parameters, BFGSSpace::Running, BFGSSpace::Success, BFGS< FunctorType >::testGradient(), pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::tmp_idx_src_, pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::tmp_idx_tgt_, pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::tmp_src_, and pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::tmp_tgt_.

template<typename PointSource, typename PointTarget>
int pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::getCorrespondenceRandomness (  )  [inline]

Get the number of neighbors used when computing covariances as set by the user.

Definition at line 219 of file gicp.h.

References pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::k_correspondences_.

template<typename PointSource, typename PointTarget>
int pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::getMaximumOptimizerIterations (  )  [inline]
Returns:
maximum number of iterations at the optimization step

Definition at line 229 of file gicp.h.

References pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::max_inner_iterations_.

template<typename PointSource, typename PointTarget>
double pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::getRotationEpsilon (  )  [inline]

Get the rotation epsilon (maximum allowable difference between two consecutive rotations) as set by the user.

Definition at line 204 of file gicp.h.

References pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::rotation_epsilon_.

template<typename PointSource, typename PointTarget>
const Eigen::Matrix3d& pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::mahalanobis ( size_t  index  )  const [inline]
Returns:
Mahalanobis distance matrix for the given point index

Definition at line 176 of file gicp.h.

References pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::mahalanobis_.

Referenced by pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::OptimizationFunctorWithIndices::df(), pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::OptimizationFunctorWithIndices::fdf(), and pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::OptimizationFunctorWithIndices::operator()().

template<typename PointSource, typename PointTarget>
double pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::matricesInnerProd ( const Eigen::MatrixXd &  mat1,
const Eigen::MatrixXd &  mat2 
) const [inline, protected]
Returns:
trace of mat1^t . mat2
Parameters:
mat1 matrix of dimension nxm
mat2 matrix of dimension nxp

Definition at line 294 of file gicp.h.

Referenced by pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::computeRDerivative().

template<typename PointSource, typename PointTarget>
pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::PCL_DEPRECATED ( void   setInputCloudconst PointCloudSourceConstPtr &cloud,
" setInputCloud is deprecated. Please use setInputSource instead."  [pcl::registration::GeneralizedIterativeClosestPoint::setInputCloud] 
)

Provide a pointer to the input dataset.

Parameters:
cloud the const boost shared pointer to a PointCloud message
template<typename PointSource, typename PointTarget>
bool pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::searchForNeighbors ( const PointSource &  query,
std::vector< int > &  index,
std::vector< float > &  distance 
) [inline, protected]

Search for the closest nearest neighbor of a given point.

Parameters:
query the point to search a nearest neighbour for
index vector of size 1 to store the index of the nearest neighbour found
distance vector of size 1 to store the distance to nearest neighbour found

Definition at line 318 of file gicp.h.

References pcl::Registration< PointSource, PointTarget, float >::tree_.

Referenced by pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::computeTransformation().

template<typename PointSource, typename PointTarget>
void pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::setCorrespondenceRandomness ( int  k  )  [inline]

Set the number of neighbors used when selecting a point neighbourhood to compute covariances.

A higher value will bring more accurate covariance matrix but will make covariances computation slower.

Parameters:
k the number of neighbors to use when computing covariances

Definition at line 213 of file gicp.h.

References pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::k_correspondences_.

template<typename PointSource, typename PointTarget>
void pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::setInputSource ( const PointCloudSourceConstPtr &  cloud  )  [inline, virtual]

Provide a pointer to the input dataset.

Parameters:
cloud the const boost shared pointer to a PointCloud message

Reimplemented from pcl::IterativeClosestPoint< PointSource, PointTarget >.

Definition at line 131 of file gicp.h.

References pcl::Registration< PointSource, PointTarget, float >::getClassName(), pcl::PCLBase< PointSource >::input_, pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::input_covariances_, and pcl::PointCloud< PointT >::size().

template<typename PointSource, typename PointTarget>
void pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::setInputTarget ( const PointCloudTargetConstPtr &  target  )  [inline, virtual]

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

Parameters:
[in] target the input point cloud target

Reimplemented from pcl::IterativeClosestPoint< PointSource, PointTarget >.

Definition at line 153 of file gicp.h.

References pcl::Registration< PointSource, PointTarget, float >::target_, and pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::target_covariances_.

template<typename PointSource, typename PointTarget>
void pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::setMaximumOptimizerIterations ( int  max  )  [inline]

set maximum number of iterations at the optimization step

Parameters:
[in] max maximum number of iterations for the optimizer

Definition at line 225 of file gicp.h.

References pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::max_inner_iterations_.

template<typename PointSource, typename PointTarget>
void pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::setRotationEpsilon ( double  epsilon  )  [inline]

Set the rotation epsilon (maximum allowable difference between two consecutive rotations) in order for an optimization to be considered as having converged to the final solution.

Parameters:
epsilon the rotation epsilon

Definition at line 198 of file gicp.h.

References pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::rotation_epsilon_.

Member Data Documentation

template<typename PointSource, typename PointTarget>
Eigen::Matrix4f pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::base_transformation_ [protected]

base transformation

Definition at line 251 of file gicp.h.

Referenced by pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::computeTransformation(), pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::OptimizationFunctorWithIndices::df(), pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::OptimizationFunctorWithIndices::fdf(), and pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::OptimizationFunctorWithIndices::operator()().

template<typename PointSource, typename PointTarget>
double pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::gicp_epsilon_ [protected]

The epsilon constant for gicp paper; this is NOT the convergence tolerence default: 0.001.

Definition at line 242 of file gicp.h.

Referenced by pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::computeCovariances().

template<typename PointSource, typename PointTarget>
std::vector<Eigen::Matrix3d> pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::input_covariances_ [protected]

Input cloud points covariances.

Definition at line 267 of file gicp.h.

Referenced by pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::computeTransformation(), and pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::setInputSource().

template<typename PointSource, typename PointTarget>
int pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::k_correspondences_ [protected]

The number of neighbors used for covariances computation.

default: 20

Definition at line 236 of file gicp.h.

Referenced by pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::computeCovariances(), pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::getCorrespondenceRandomness(), and pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::setCorrespondenceRandomness().

template<typename PointSource, typename PointTarget>
std::vector<Eigen::Matrix3d> pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::mahalanobis_ [protected]

Mahalanobis matrices holder.

Definition at line 273 of file gicp.h.

Referenced by pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::computeTransformation(), and pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::mahalanobis().

template<typename PointSource, typename PointTarget>
int pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::max_inner_iterations_ [protected]

maximum number of optimizations

Definition at line 276 of file gicp.h.

Referenced by pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::estimateRigidTransformationBFGS(), pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::getMaximumOptimizerIterations(), and pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::setMaximumOptimizerIterations().

template<typename PointSource, typename PointTarget>
boost::function<void(const pcl::PointCloud<PointSource> &cloud_src, const std::vector<int> &src_indices, const pcl::PointCloud<PointTarget> &cloud_tgt, const std::vector<int> &tgt_indices, Eigen::Matrix4f &transformation_matrix)> pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::rigid_transformation_estimation_ [protected]

Definition at line 345 of file gicp.h.

Referenced by pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::computeTransformation(), and pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::GeneralizedIterativeClosestPoint().

template<typename PointSource, typename PointTarget>
double pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::rotation_epsilon_ [protected]

The epsilon constant for rotation error.

(In GICP the transformation epsilon is split in rotation part and translation part). default: 2e-3

Definition at line 248 of file gicp.h.

Referenced by pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::computeTransformation(), pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::getRotationEpsilon(), and pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::setRotationEpsilon().

template<typename PointSource, typename PointTarget>
std::vector<Eigen::Matrix3d> pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::target_covariances_ [protected]

Target cloud points covariances.

Definition at line 270 of file gicp.h.

Referenced by pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::computeTransformation(), and pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::setInputTarget().

template<typename PointSource, typename PointTarget>
const std::vector<int>* pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::tmp_idx_src_ [protected]

Temporary pointer to the source dataset indices.

Definition at line 260 of file gicp.h.

Referenced by pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::OptimizationFunctorWithIndices::df(), pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::estimateRigidTransformationBFGS(), pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::OptimizationFunctorWithIndices::fdf(), and pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::OptimizationFunctorWithIndices::operator()().

template<typename PointSource, typename PointTarget>
const std::vector<int>* pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::tmp_idx_tgt_ [protected]

Temporary pointer to the target dataset indices.

Definition at line 263 of file gicp.h.

Referenced by pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::OptimizationFunctorWithIndices::df(), pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::estimateRigidTransformationBFGS(), pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::OptimizationFunctorWithIndices::fdf(), and pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::OptimizationFunctorWithIndices::operator()().

template<typename PointSource, typename PointTarget>
const PointCloudSource* pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::tmp_src_ [protected]

Temporary pointer to the source dataset.

Definition at line 254 of file gicp.h.

Referenced by pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::OptimizationFunctorWithIndices::df(), pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::estimateRigidTransformationBFGS(), pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::OptimizationFunctorWithIndices::fdf(), and pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::OptimizationFunctorWithIndices::operator()().

template<typename PointSource, typename PointTarget>
const PointCloudTarget* pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::tmp_tgt_ [protected]

Temporary pointer to the target dataset.

Definition at line 257 of file gicp.h.

Referenced by pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::OptimizationFunctorWithIndices::df(), pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::estimateRigidTransformationBFGS(), pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::OptimizationFunctorWithIndices::fdf(), and pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::OptimizationFunctorWithIndices::operator()().

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