Point Cloud Library (PCL) 1.14.0
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transformation_estimation_3point.hpp
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37#ifndef PCL_REGISTRATION_IMPL_TRANSFORMATION_ESTIMATION_3POINT_H_
38#define PCL_REGISTRATION_IMPL_TRANSFORMATION_ESTIMATION_3POINT_H_
39
40#include <pcl/common/eigen.h>
41#include <pcl/registration/transformation_estimation_3point.h>
42
43///////////////////////////////////////////////////////////////////////////////////////////
44template <typename PointSource, typename PointTarget, typename Scalar>
45inline void
48 const pcl::PointCloud<PointTarget>& cloud_tgt,
49 Matrix4& transformation_matrix) const
50{
51 if (cloud_src.size() != 3 || cloud_tgt.size() != 3) {
52 PCL_ERROR("[pcl::TransformationEstimation3Point::estimateRigidTransformation] "
53 "Number of points in source (%zu) and target (%zu) must be 3!\n",
54 static_cast<std::size_t>(cloud_src.size()),
55 static_cast<std::size_t>(cloud_tgt.size()));
56 return;
57 }
58
59 ConstCloudIterator<PointSource> source_it(cloud_src);
60 ConstCloudIterator<PointTarget> target_it(cloud_tgt);
61 estimateRigidTransformation(source_it, target_it, transformation_matrix);
62}
63
64///////////////////////////////////////////////////////////////////////////////////////////
65template <typename PointSource, typename PointTarget, typename Scalar>
66void
69 const pcl::Indices& indices_src,
70 const pcl::PointCloud<PointTarget>& cloud_tgt,
71 Matrix4& transformation_matrix) const
72{
73 if (indices_src.size() != 3 || cloud_tgt.size() != 3) {
74 PCL_ERROR(
75 "[pcl::TransformationEstimation3Point::estimateRigidTransformation] Number of "
76 "indices in source (%zu) and points in target (%zu) must be 3!\n",
77 indices_src.size(),
78 static_cast<std::size_t>(cloud_tgt.size()));
79 return;
80 }
81
82 ConstCloudIterator<PointSource> source_it(cloud_src, indices_src);
83 ConstCloudIterator<PointTarget> target_it(cloud_tgt);
84 estimateRigidTransformation(source_it, target_it, transformation_matrix);
85}
86
87///////////////////////////////////////////////////////////////////////////////////////////
88template <typename PointSource, typename PointTarget, typename Scalar>
89inline void
92 const pcl::Indices& indices_src,
93 const pcl::PointCloud<PointTarget>& cloud_tgt,
94 const pcl::Indices& indices_tgt,
95 Matrix4& transformation_matrix) const
96{
97 if (indices_src.size() != 3 || indices_tgt.size() != 3) {
98 PCL_ERROR("[pcl::TransformationEstimation3Point::estimateRigidTransformation] "
99 "Number of indices in source (%lu) and target (%lu) must be 3!\n",
100 indices_src.size(),
101 indices_tgt.size());
102 return;
103 }
104
105 ConstCloudIterator<PointSource> source_it(cloud_src, indices_src);
106 ConstCloudIterator<PointTarget> target_it(cloud_tgt, indices_tgt);
107 estimateRigidTransformation(source_it, target_it, transformation_matrix);
108}
109
110///////////////////////////////////////////////////////////////////////////////////////////
111template <typename PointSource, typename PointTarget, typename Scalar>
112void
115 const pcl::PointCloud<PointTarget>& cloud_tgt,
116 const pcl::Correspondences& correspondences,
117 Matrix4& transformation_matrix) const
118{
119 if (correspondences.size() != 3) {
120 PCL_ERROR("[pcl::TransformationEstimation3Point::estimateRigidTransformation] "
121 "Number of correspondences (%lu) must be 3!\n",
122 correspondences.size());
123 return;
124 }
125
126 ConstCloudIterator<PointSource> source_it(cloud_src, correspondences, true);
127 ConstCloudIterator<PointTarget> target_it(cloud_tgt, correspondences, false);
128 estimateRigidTransformation(source_it, target_it, transformation_matrix);
129}
130
131///////////////////////////////////////////////////////////////////////////////////////////
132template <typename PointSource, typename PointTarget, typename Scalar>
133inline void
137 Matrix4& transformation_matrix) const
138{
139 transformation_matrix.setIdentity();
140 source_it.reset();
141 target_it.reset();
142
143 Eigen::Matrix<Scalar, 4, 1> source_mean, target_mean;
144 pcl::compute3DCentroid(source_it, source_mean);
145 pcl::compute3DCentroid(target_it, target_mean);
146
147 source_it.reset();
148 target_it.reset();
149
150 Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic> source_demean, target_demean;
151 pcl::demeanPointCloud(source_it, source_mean, source_demean, 3);
152 pcl::demeanPointCloud(target_it, target_mean, target_demean, 3);
153
154 source_it.reset();
155 target_it.reset();
156
157 Eigen::Matrix<Scalar, 3, 1> s1 =
158 source_demean.col(1).head(3) - source_demean.col(0).head(3);
159 s1.normalize();
160
161 Eigen::Matrix<Scalar, 3, 1> s2 =
162 source_demean.col(2).head(3) - source_demean.col(0).head(3);
163 s2 -= s2.dot(s1) * s1;
164 s2.normalize();
165
166 Eigen::Matrix<Scalar, 3, 3> source_rot;
167 source_rot.col(0) = s1;
168 source_rot.col(1) = s2;
169 source_rot.col(2) = s1.cross(s2);
170
171 Eigen::Matrix<Scalar, 3, 1> t1 =
172 target_demean.col(1).head(3) - target_demean.col(0).head(3);
173 t1.normalize();
174
175 Eigen::Matrix<Scalar, 3, 1> t2 =
176 target_demean.col(2).head(3) - target_demean.col(0).head(3);
177 t2 -= t2.dot(t1) * t1;
178 t2.normalize();
179
180 Eigen::Matrix<Scalar, 3, 3> target_rot;
181 target_rot.col(0) = t1;
182 target_rot.col(1) = t2;
183 target_rot.col(2) = t1.cross(t2);
184
185 // Eigen::Matrix <Scalar, 3, 3> R = source_rot * target_rot.transpose ();
186 Eigen::Matrix<Scalar, 3, 3> R = target_rot * source_rot.transpose();
187 transformation_matrix.topLeftCorner(3, 3) = R;
188 // transformation_matrix.block (0, 3, 3, 1) = source_mean.head (3) - R *
189 // target_mean.head (3);
190 transformation_matrix.block(0, 3, 3, 1) =
191 target_mean.head(3) - R * source_mean.head(3);
192}
193
194//#define PCL_INSTANTIATE_TransformationEstimation3Point(T,U) template class PCL_EXPORTS
195// pcl::registration::TransformationEstimation3Point<T,U>;
196
197#endif // PCL_REGISTRATION_IMPL_TRANSFORMATION_ESTIMATION_3POINT_H_
Iterator class for point clouds with or without given indices.
PointCloud represents the base class in PCL for storing collections of 3D points.
std::size_t size() const
void estimateRigidTransformation(const pcl::PointCloud< PointSource > &cloud_src, const pcl::Indices &indices_src, const pcl::PointCloud< PointTarget > &cloud_tgt, const pcl::Indices &indices_tgt, Matrix4 &transformation_matrix) const override
Estimate a rigid rotation transformation between a source and a target point cloud.
void estimateRigidTransformation(const pcl::PointCloud< PointSource > &cloud_src, const pcl::PointCloud< PointTarget > &cloud_tgt, Matrix4 &transformation_matrix) const override
Estimate a rigid rotation transformation between a source and a target point cloud.
void demeanPointCloud(ConstCloudIterator< PointT > &cloud_iterator, const Eigen::Matrix< Scalar, 4, 1 > &centroid, pcl::PointCloud< PointT > &cloud_out, int npts=0)
Subtract a centroid from a point cloud and return the de-meaned representation.
Definition centroid.hpp:933
unsigned int compute3DCentroid(ConstCloudIterator< PointT > &cloud_iterator, Eigen::Matrix< Scalar, 4, 1 > &centroid)
Compute the 3D (X-Y-Z) centroid of a set of points and return it as a 3D vector.
Definition centroid.hpp:57
std::vector< pcl::Correspondence, Eigen::aligned_allocator< pcl::Correspondence > > Correspondences
IndicesAllocator<> Indices
Type used for indices in PCL.
Definition types.h:133