Point Cloud Library (PCL) 1.14.0
Loading...
Searching...
No Matches
transformation_estimation_2D.h
1/*
2 * Software License Agreement (BSD License)
3 *
4 * Point Cloud Library (PCL) - www.pointclouds.org
5 * Copyright (c) 2012-, Open Perception Inc.
6 *
7 * All rights reserved.
8 *
9 * Redistribution and use in source and binary forms, with or without
10 * modification, are permitted provided that the following conditions
11 * are met:
12 *
13 * * Redistributions of source code must retain the above copyright
14 * notice, this list of conditions and the following disclaimer.
15 * * Redistributions in binary form must reproduce the above
16 * copyright notice, this list of conditions and the following
17 * disclaimer in the documentation and/or other materials provided
18 * with the distribution.
19 * * Neither the name of the copyright holder(s) nor the names of its
20 * contributors may be used to endorse or promote products derived
21 * from this software without specific prior written permission.
22 *
23 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
24 * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
25 * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
26 * FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
27 * COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
28 * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
29 * BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
30 * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
31 * CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
32 * LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
33 * ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
34 * POSSIBILITY OF SUCH DAMAGE.
35 *
36 *
37 */
38
39#pragma once
40
41#include <pcl/registration/transformation_estimation.h>
42
43namespace pcl {
44namespace registration {
45/** @b TransformationEstimation2D implements a simple 2D rigid transformation
46 * estimation (x, y, theta) for a given pair of datasets.
47 *
48 * The two datasets should already be transformed so that the reference plane
49 * equals z = 0.
50 *
51 * \note The class is templated on the source and target point types as well as on the
52 * output scalar of the transformation matrix (i.e., float or double). Default: float.
53 *
54 * \author Suat Gedikli
55 * \ingroup registration
56 */
57template <typename PointSource, typename PointTarget, typename Scalar = float>
59: public TransformationEstimation<PointSource, PointTarget, Scalar> {
60public:
61 using Ptr = shared_ptr<TransformationEstimation2D<PointSource, PointTarget, Scalar>>;
62 using ConstPtr =
63 shared_ptr<const TransformationEstimation2D<PointSource, PointTarget, Scalar>>;
64
65 using Matrix4 =
67
69 virtual ~TransformationEstimation2D() = default;
70
71 /** \brief Estimate a rigid transformation between a source and a target point cloud
72 * in 2D. \param[in] cloud_src the source point cloud dataset \param[in] cloud_tgt the
73 * target point cloud dataset \param[out] transformation_matrix the resultant
74 * transformation matrix
75 */
76 inline void
78 const pcl::PointCloud<PointTarget>& cloud_tgt,
79 Matrix4& transformation_matrix) const;
80
81 /** \brief Estimate a rigid transformation between a source and a target point cloud
82 * in 2D. \param[in] cloud_src the source point cloud dataset \param[in] indices_src
83 * the vector of indices describing the points of interest in \a cloud_src
84 * \param[in] cloud_tgt the target point cloud dataset
85 * \param[out] transformation_matrix the resultant transformation matrix
86 */
87 inline void
89 const pcl::Indices& indices_src,
90 const pcl::PointCloud<PointTarget>& cloud_tgt,
91 Matrix4& transformation_matrix) const;
92
93 /** \brief Estimate a rigid transformation between a source and a target point cloud
94 * in 2D. \param[in] cloud_src the source point cloud dataset \param[in] indices_src
95 * the vector of indices describing the points of interest in \a cloud_src
96 * \param[in] cloud_tgt the target point cloud dataset
97 * \param[in] indices_tgt the vector of indices describing the correspondences of the
98 * interest points from \a indices_src
99 * \param[out] transformation_matrix the resultant transformation matrix
100 */
101 virtual void
103 const pcl::Indices& indices_src,
104 const pcl::PointCloud<PointTarget>& cloud_tgt,
105 const pcl::Indices& indices_tgt,
106 Matrix4& transformation_matrix) const;
107
108 /** \brief Estimate a rigid transformation between a source and a target point cloud
109 * in 2D. \param[in] cloud_src the source point cloud dataset \param[in] cloud_tgt the
110 * target point cloud dataset \param[in] correspondences the vector of correspondences
111 * between source and target point cloud \param[out] transformation_matrix the
112 * resultant transformation matrix
113 */
114 virtual void
116 const pcl::PointCloud<PointTarget>& cloud_tgt,
117 const pcl::Correspondences& correspondences,
118 Matrix4& transformation_matrix) const;
119
120protected:
121 /** \brief Estimate a rigid rotation transformation between a source and a target
122 * \param[in] source_it an iterator over the source point cloud dataset
123 * \param[in] target_it an iterator over the target point cloud dataset
124 * \param[out] transformation_matrix the resultant transformation matrix
125 */
126 void
129 Matrix4& transformation_matrix) const;
130
131 /** \brief Obtain a 4x4 rigid transformation matrix from a correlation matrix H = src
132 * * tgt' \param[in] cloud_src_demean the input source cloud, demeaned, in Eigen
133 * format \param[in] centroid_src the input source centroid, in Eigen format
134 * \param[in] cloud_tgt_demean the input target cloud, demeaned, in Eigen format
135 * \param[in] centroid_tgt the input target cloud, in Eigen format
136 * \param[out] transformation_matrix the resultant 4x4 rigid transformation matrix
137 */
138 void
140 const Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic>& cloud_src_demean,
141 const Eigen::Matrix<Scalar, 4, 1>& centroid_src,
142 const Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic>& cloud_tgt_demean,
143 const Eigen::Matrix<Scalar, 4, 1>& centroid_tgt,
144 Matrix4& transformation_matrix) const;
145};
146
147} // namespace registration
148} // namespace pcl
149
150#include <pcl/registration/impl/transformation_estimation_2D.hpp>
Iterator class for point clouds with or without given indices.
PointCloud represents the base class in PCL for storing collections of 3D points.
TransformationEstimation2D implements a simple 2D rigid transformation estimation (x,...
void getTransformationFromCorrelation(const Eigen::Matrix< Scalar, Eigen::Dynamic, Eigen::Dynamic > &cloud_src_demean, const Eigen::Matrix< Scalar, 4, 1 > &centroid_src, const Eigen::Matrix< Scalar, Eigen::Dynamic, Eigen::Dynamic > &cloud_tgt_demean, const Eigen::Matrix< Scalar, 4, 1 > &centroid_tgt, Matrix4 &transformation_matrix) const
Obtain a 4x4 rigid transformation matrix from a correlation matrix H = src.
void estimateRigidTransformation(const pcl::PointCloud< PointSource > &cloud_src, const pcl::PointCloud< PointTarget > &cloud_tgt, Matrix4 &transformation_matrix) const
Estimate a rigid transformation between a source and a target point cloud in 2D.
typename TransformationEstimation< PointSource, PointTarget, Scalar >::Matrix4 Matrix4
shared_ptr< const TransformationEstimation2D< PointSource, PointTarget, Scalar > > ConstPtr
shared_ptr< TransformationEstimation2D< PointSource, PointTarget, Scalar > > Ptr
TransformationEstimation represents the base class for methods for transformation estimation based on...
std::vector< pcl::Correspondence, Eigen::aligned_allocator< pcl::Correspondence > > Correspondences
IndicesAllocator<> Indices
Type used for indices in PCL.
Definition types.h:133