Point Cloud Library (PCL)
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include
pcl
registration
icp_nl.h
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/*
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* Software License Agreement (BSD License)
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*
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* Point Cloud Library (PCL) - www.pointclouds.org
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* Copyright (c) 2010-2011, Willow Garage, Inc.
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* Copyright (c) 2012-, Open Perception, Inc.
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*
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* All rights reserved.
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions
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* are met:
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* * Redistributions of source code must retain the above copyright
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* notice, this list of conditions and the following disclaimer.
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* copyright notice, this list of conditions and the following
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* with the distribution.
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* contributors may be used to endorse or promote products derived
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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* $Id$
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*
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*/
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#ifndef PCL_ICP_NL_H_
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#define PCL_ICP_NL_H_
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// PCL includes
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#include <pcl/registration/icp.h>
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#include <pcl/registration/transformation_estimation_lm.h>
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namespace
pcl
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{
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/** \brief @b IterativeClosestPointNonLinear is an ICP variant that uses Levenberg-Marquardt optimization
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* backend. The resultant transformation is optimized as a quaternion.
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*
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* The algorithm has several termination criteria:
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*
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* <ol>
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* <li>Number of iterations has reached the maximum user imposed number of iterations
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* (via \ref setMaximumIterations)</li>
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* <li>The epsilon (difference) between the previous transformation and the current estimated transformation is
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* smaller than an user imposed value (via \ref setTransformationEpsilon)</li>
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* <li>The sum of Euclidean squared errors is smaller than a user defined threshold
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* (via \ref setEuclideanFitnessEpsilon)</li>
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* </ol>
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*
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* \author Radu B. Rusu, Michael Dixon
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* \ingroup registration
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*/
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template
<
typename
Po
int
Source,
typename
Po
int
Target,
typename
Scalar =
float
>
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class
IterativeClosestPointNonLinear
:
public
IterativeClosestPoint
<PointSource, PointTarget, Scalar>
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{
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using
IterativeClosestPoint<PointSource, PointTarget, Scalar>::min_number_correspondences_
;
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using
IterativeClosestPoint<PointSource, PointTarget, Scalar>::reg_name_
;
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using
IterativeClosestPoint<PointSource, PointTarget, Scalar>::transformation_estimation_
;
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using
IterativeClosestPoint<PointSource, PointTarget, Scalar>::computeTransformation
;
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public
:
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typedef
boost::shared_ptr< IterativeClosestPointNonLinear<PointSource, PointTarget, Scalar> >
Ptr
;
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typedef
boost::shared_ptr< const IterativeClosestPointNonLinear<PointSource, PointTarget, Scalar> >
ConstPtr
;
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typedef
typename
Registration<PointSource, PointTarget, Scalar>::Matrix4
Matrix4
;
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/** \brief Empty constructor. */
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IterativeClosestPointNonLinear
()
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{
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min_number_correspondences_
= 4;
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reg_name_
=
"IterativeClosestPointNonLinear"
;
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transformation_estimation_
.reset (
new
pcl::registration::TransformationEstimationLM<PointSource, PointTarget, Scalar>
);
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}
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};
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}
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#endif //#ifndef PCL_ICP_NL_H_