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4PCS for initial pairwise point cloud registration
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theilerp committed Jan 12, 2015
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572 changes: 572 additions & 0 deletions registration/include/pcl/registration/ia_fpcs.h

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912 changes: 912 additions & 0 deletions registration/include/pcl/registration/impl/ia_fpcs.hpp

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/*
* Software License Agreement (BSD License)
*
* Point Cloud Library (PCL) - www.pointclouds.org
* Copyright (c) 2014-, Open Perception, Inc.
*
* All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
*
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above
* copyright notice, this list of conditions and the following
* disclaimer in the documentation and/or other materials provided
* with the distribution.
* * Neither the name of the copyright holder(s) nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
* POSSIBILITY OF SUCH DAMAGE.
*
* $Id: transformation_estimation_3point.hpp 2014 P.W.Theiler$
*
*/
#ifndef PCL_REGISTRATION_IMPL_TRANSFORMATION_ESTIMATION_3POINT_H_
#define PCL_REGISTRATION_IMPL_TRANSFORMATION_ESTIMATION_3POINT_H_

#include <pcl/common/eigen.h>
#include <pcl/registration/transformation_estimation_3point.h>

///////////////////////////////////////////////////////////////////////////////////////////
template <typename PointSource, typename PointTarget, typename Scalar> inline void
pcl::registration::TransformationEstimation3Point<PointSource, PointTarget, Scalar>::estimateRigidTransformation (
const pcl::PointCloud<PointSource> &cloud_src,
const pcl::PointCloud<PointTarget> &cloud_tgt,
Matrix4 &transformation_matrix) const
{
if (cloud_src.points.size () != 3 || cloud_tgt.points.size () != 3)
{
PCL_ERROR ("[pcl::TransformationEstimation3Point::estimateRigidTransformation] Number of points in source (%lu) and target (%lu) must be 3!\n",
cloud_src.points.size (), cloud_tgt.points.size ());
return;
}

ConstCloudIterator<PointSource> source_it (cloud_src);
ConstCloudIterator<PointTarget> target_it (cloud_tgt);
estimateRigidTransformation (source_it, target_it, transformation_matrix);
}

///////////////////////////////////////////////////////////////////////////////////////////
template <typename PointSource, typename PointTarget, typename Scalar> void
pcl::registration::TransformationEstimation3Point<PointSource, PointTarget, Scalar>::estimateRigidTransformation (
const pcl::PointCloud<PointSource> &cloud_src,
const std::vector<int> &indices_src,
const pcl::PointCloud<PointTarget> &cloud_tgt,
Matrix4 &transformation_matrix) const
{
if (indices_src.size () != 3 || cloud_tgt.points.size () != 3)
{
PCL_ERROR ("[pcl::TransformationEstimation3Point::estimateRigidTransformation] Number of indices in source (%lu) and points in target (%lu) must be 3!\n",
indices_src.size (), cloud_tgt.points.size ());
return;
}

ConstCloudIterator<PointSource> source_it (cloud_src, indices_src);
ConstCloudIterator<PointTarget> target_it (cloud_tgt);
estimateRigidTransformation (source_it, target_it, transformation_matrix);
}

///////////////////////////////////////////////////////////////////////////////////////////
template <typename PointSource, typename PointTarget, typename Scalar> inline void
pcl::registration::TransformationEstimation3Point<PointSource, PointTarget, Scalar>::estimateRigidTransformation (
const pcl::PointCloud<PointSource> &cloud_src,
const std::vector<int> &indices_src,
const pcl::PointCloud<PointTarget> &cloud_tgt,
const std::vector<int> &indices_tgt,
Matrix4 &transformation_matrix) const
{
if (indices_src.size () != 3 || indices_tgt.size () != 3)
{
PCL_ERROR ("[pcl::TransformationEstimation3Point::estimateRigidTransformation] Number of indices in source (%lu) and target (%lu) must be 3!\n",
indices_src.size (), indices_tgt.size ());
return;
}

ConstCloudIterator<PointSource> source_it (cloud_src, indices_src);
ConstCloudIterator<PointTarget> target_it (cloud_tgt, indices_tgt);
estimateRigidTransformation (source_it, target_it, transformation_matrix);
}

///////////////////////////////////////////////////////////////////////////////////////////
template <typename PointSource, typename PointTarget, typename Scalar> void
pcl::registration::TransformationEstimation3Point<PointSource, PointTarget, Scalar>::estimateRigidTransformation (
const pcl::PointCloud<PointSource> &cloud_src,
const pcl::PointCloud<PointTarget> &cloud_tgt,
const pcl::Correspondences &correspondences,
Matrix4 &transformation_matrix) const
{
if (correspondences.size () != 3)
{
PCL_ERROR ("[pcl::TransformationEstimation3Point::estimateRigidTransformation] Number of correspondences (%lu) must be 3!\n",
correspondences.size ());
return;
}

ConstCloudIterator<PointSource> source_it (cloud_src, correspondences, true);
ConstCloudIterator<PointTarget> target_it (cloud_tgt, correspondences, false);
estimateRigidTransformation (source_it, target_it, transformation_matrix);
}

///////////////////////////////////////////////////////////////////////////////////////////
template <typename PointSource, typename PointTarget, typename Scalar> inline void
pcl::registration::TransformationEstimation3Point<PointSource, PointTarget, Scalar>::estimateRigidTransformation (
ConstCloudIterator<PointSource>& source_it,
ConstCloudIterator<PointTarget>& target_it,
Matrix4 &transformation_matrix) const
{
transformation_matrix.setIdentity ();
source_it.reset ();
target_it.reset ();

Eigen::Matrix <Scalar, 4, 1> source_mean, target_mean;
pcl::compute3DCentroid (source_it, source_mean);
pcl::compute3DCentroid (target_it, target_mean);

source_it.reset ();
target_it.reset ();

Eigen::Matrix <Scalar, Eigen::Dynamic, Eigen::Dynamic> source_demean, target_demean;
pcl::demeanPointCloud (source_it, source_mean, source_demean, 3);
pcl::demeanPointCloud (target_it, target_mean, target_demean, 3);

source_it.reset ();
target_it.reset ();

Eigen::Matrix <Scalar, 3, 1> s1 = source_demean.col (1).head (3) - source_demean.col (0).head (3);
s1.normalize ();

Eigen::Matrix <Scalar, 3, 1> s2 = source_demean.col (2).head (3) - source_demean.col (0).head (3);
s2 -= s2.dot (s1) * s1;
s2.normalize ();

Eigen::Matrix <Scalar, 3, 3> source_rot;
source_rot.col (0) = s1;
source_rot.col (1) = s2;
source_rot.col (2) = s1.cross (s2);

Eigen::Matrix <Scalar, 3, 1> t1 = target_demean.col (1).head (3) - target_demean.col (0).head (3);
t1.normalize ();

Eigen::Matrix <Scalar, 3, 1> t2 = target_demean.col (2).head (3) - target_demean.col (0).head (3);
t2 -= t2.dot (t1) * t1;
t2.normalize ();

Eigen::Matrix <Scalar, 3, 3> target_rot;
target_rot.col (0) = t1;
target_rot.col (1) = t2;
target_rot.col (2) = t1.cross (t2);

//Eigen::Matrix <Scalar, 3, 3> R = source_rot * target_rot.transpose ();
Eigen::Matrix <Scalar, 3, 3> R = target_rot * source_rot.transpose ();
transformation_matrix.topLeftCorner (3, 3) = R;
//transformation_matrix.block (0, 3, 3, 1) = source_mean.head (3) - R * target_mean.head (3);
transformation_matrix.block (0, 3, 3, 1) = target_mean.head (3) - R * source_mean.head (3);
}

//#define PCL_INSTANTIATE_TransformationEstimation3Point(T,U) template class PCL_EXPORTS pcl::registration::TransformationEstimation3Point<T,U>;

#endif // PCL_REGISTRATION_IMPL_TRANSFORMATION_ESTIMATION_3POINT_H_
102 changes: 102 additions & 0 deletions registration/include/pcl/registration/matching_candidate.h
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/*
* Software License Agreement (BSD License)
*
* Point Cloud Library (PCL) - www.pointclouds.org
* Copyright (c) 2014-, Open Perception, Inc.
* Copyright (C) 2008 Ben Gurion University of the Negev, Beer Sheva, Israel.
*
* All rights reserved
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions are met
*
* * The use for research only (no for any commercial application).
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above
* copyright notice, this list of conditions and the following
* disclaimer in the documentation and/or other materials provided
* with the distribution.
* * Neither the name of the copyright holder(s) nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
* POSSIBILITY OF SUCH DAMAGE.
*
* $Id: matching_candidate.h 2014 P.W.Theiler$
*
*/

#ifndef PCL_REGISTRATION_MATCHING_CANDIDATE_H_
#define PCL_REGISTRATION_MATCHING_CANDIDATE_H_

#include <pcl/registration/registration.h>
#include <pcl/common/common.h>

namespace pcl
{
namespace registration
{
/** \brief Container for matching candidate consisting of
*
* * fitness score value as a result of the matching algorithm
* * correspondences between source and target data set
* * transformation matrix calculated based on the correspondences
*
*/
struct MatchingCandidate
{
/** \brief Default constructor. */
MatchingCandidate () :
fitness_score (FLT_MAX),
correspondences (),
transformation (Eigen::Matrix4f::Identity ())
{};

/** \brief Value constructor. */
MatchingCandidate (float s, const pcl::Correspondences &c, const Eigen::Matrix4f &m) :
fitness_score (s),
correspondences (c),
transformation (m)
{};

/** \brief Default destructor. */
~MatchingCandidate ()
{};


/** \brief Fitness score of current candidate resulting from matching algorithm. */
float fitness_score;

/** \brief Correspondences between source <-> target. */
pcl::Correspondences correspondences;

/** \brief Corresponding transformation matrix retrieved using \a corrs. */
Eigen::Matrix4f transformation;
};

/** \brief Sorting of candidates based on fitness score value. */
struct by_score
{
bool operator () (MatchingCandidate const &left, MatchingCandidate const &right)
{
return (left.fitness_score < right.fitness_score);
}
};

}; // namespace registration
}; // namespace pcl


#endif // PCL_REGISTRATION_MATCHING_CANDIDATE_H_
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