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 >:

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List of all members.

Public Member Functions
	IterativeClosestPoint ()
	Empty constructor.
Protected Member Functions
virtual void	computeTransformation (PointCloudSource &output, const Eigen::Matrix4f &guess)
	Rigid transformation computation method with initial guess.
Private Types
typedef Registration < PointSource, PointTarget > ::PointCloudSource	PointCloudSource
typedef PointCloudSource::ConstPtr	PointCloudSourceConstPtr
typedef PointCloudSource::Ptr	PointCloudSourcePtr
typedef Registration < PointSource, PointTarget > ::PointCloudTarget	PointCloudTarget
typedef PointIndices::ConstPtr	PointIndicesConstPtr
typedef PointIndices::Ptr	PointIndicesPtr

Detailed Description

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

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 Bogdan Rusu, Michael Dixon

Definition at line 88 of file icp.h.