Point Cloud Library (PCL) 1.12.0
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transformation_estimation_dq.hpp
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39
40#ifndef PCL_REGISTRATION_TRANSFORMATION_ESTIMATION_DQ_HPP_
41#define PCL_REGISTRATION_TRANSFORMATION_ESTIMATION_DQ_HPP_
42
43#include <pcl/common/eigen.h>
45 15,
46 "TransformationEstimationDQ has been renamed to "
47 "TransformationEstimationDualQuaternion.");
48
49namespace pcl {
50
51namespace registration {
52
53template <typename PointSource, typename PointTarget, typename Scalar>
54inline void
57 const pcl::PointCloud<PointTarget>& cloud_tgt,
58 Matrix4& transformation_matrix) const
59{
60 const auto nr_points = cloud_src.size();
61 if (cloud_tgt.size() != nr_points) {
62 PCL_ERROR("[pcl::TransformationEstimationDQ::estimateRigidTransformation] Number "
63 "or points in source (%zu) differs than target (%zu)!\n",
64 static_cast<std::size_t>(nr_points),
65 static_cast<std::size_t>(cloud_tgt.size()));
66 return;
67 }
68
69 ConstCloudIterator<PointSource> source_it(cloud_src);
70 ConstCloudIterator<PointTarget> target_it(cloud_tgt);
71 estimateRigidTransformation(source_it, target_it, transformation_matrix);
72}
73
74template <typename PointSource, typename PointTarget, typename Scalar>
75void
78 const pcl::Indices& indices_src,
79 const pcl::PointCloud<PointTarget>& cloud_tgt,
80 Matrix4& transformation_matrix) const
81{
82 if (indices_src.size() != cloud_tgt.size()) {
83 PCL_ERROR("[pcl::TransformationDQ::estimateRigidTransformation] Number or points "
84 "in source (%zu) differs than target (%zu)!\n",
85 indices_src.size(),
86 static_cast<std::size_t>(cloud_tgt.size()));
87 return;
88 }
89
90 ConstCloudIterator<PointSource> source_it(cloud_src, indices_src);
91 ConstCloudIterator<PointTarget> target_it(cloud_tgt);
92 estimateRigidTransformation(source_it, target_it, transformation_matrix);
93}
94
95template <typename PointSource, typename PointTarget, typename Scalar>
96inline void
99 const pcl::Indices& indices_src,
100 const pcl::PointCloud<PointTarget>& cloud_tgt,
101 const pcl::Indices& indices_tgt,
102 Matrix4& transformation_matrix) const
103{
104 if (indices_src.size() != indices_tgt.size()) {
105 PCL_ERROR("[pcl::TransformationEstimationDQ::estimateRigidTransformation] Number "
106 "or points in source (%zu) differs than target (%zu)!\n",
107 indices_src.size(),
108 indices_tgt.size());
109 return;
110 }
111
112 ConstCloudIterator<PointSource> source_it(cloud_src, indices_src);
113 ConstCloudIterator<PointTarget> target_it(cloud_tgt, indices_tgt);
114 estimateRigidTransformation(source_it, target_it, transformation_matrix);
115}
116
117template <typename PointSource, typename PointTarget, typename Scalar>
118void
121 const pcl::PointCloud<PointTarget>& cloud_tgt,
122 const pcl::Correspondences& correspondences,
123 Matrix4& transformation_matrix) const
124{
125 ConstCloudIterator<PointSource> source_it(cloud_src, correspondences, true);
126 ConstCloudIterator<PointTarget> target_it(cloud_tgt, correspondences, false);
127 estimateRigidTransformation(source_it, target_it, transformation_matrix);
128}
129
130template <typename PointSource, typename PointTarget, typename Scalar>
131inline void
135 Matrix4& transformation_matrix) const
136{
137 const int npts = static_cast<int>(source_it.size());
138
139 transformation_matrix.setIdentity();
140
141 // dual quaternion optimization
142 Eigen::Matrix<Scalar, 4, 4> C1 = Eigen::Matrix<Scalar, 4, 4>::Zero();
143 Eigen::Matrix<Scalar, 4, 4> C2 = Eigen::Matrix<Scalar, 4, 4>::Zero();
144 Scalar* c1 = C1.data();
145 Scalar* c2 = C2.data();
146
147 for (int i = 0; i < npts; i++) {
148 const PointSource& a = *source_it;
149 const PointTarget& b = *target_it;
150 const Scalar axbx = a.x * b.x;
151 const Scalar ayby = a.y * b.y;
152 const Scalar azbz = a.z * b.z;
153 const Scalar axby = a.x * b.y;
154 const Scalar aybx = a.y * b.x;
155 const Scalar axbz = a.x * b.z;
156 const Scalar azbx = a.z * b.x;
157 const Scalar aybz = a.y * b.z;
158 const Scalar azby = a.z * b.y;
159 c1[0] += axbx - azbz - ayby;
160 c1[5] += ayby - azbz - axbx;
161 c1[10] += azbz - axbx - ayby;
162 c1[15] += axbx + ayby + azbz;
163 c1[1] += axby + aybx;
164 c1[2] += axbz + azbx;
165 c1[3] += aybz - azby;
166 c1[6] += azby + aybz;
167 c1[7] += azbx - axbz;
168 c1[11] += axby - aybx;
169
170 c2[1] += a.z + b.z;
171 c2[2] -= a.y + b.y;
172 c2[3] += a.x - b.x;
173 c2[6] += a.x + b.x;
174 c2[7] += a.y - b.y;
175 c2[11] += a.z - b.z;
176 source_it++;
177 target_it++;
178 }
179
180 c1[4] = c1[1];
181 c1[8] = c1[2];
182 c1[9] = c1[6];
183 c1[12] = c1[3];
184 c1[13] = c1[7];
185 c1[14] = c1[11];
186 c2[4] = -c2[1];
187 c2[8] = -c2[2];
188 c2[12] = -c2[3];
189 c2[9] = -c2[6];
190 c2[13] = -c2[7];
191 c2[14] = -c2[11];
192
193 C1 *= -2.0f;
194 C2 *= 2.0f;
195
196 const Eigen::Matrix<Scalar, 4, 4> A =
197 (0.25f / float(npts)) * C2.transpose() * C2 - C1;
198
199 const Eigen::EigenSolver<Eigen::Matrix<Scalar, 4, 4>> es(A);
200
201 ptrdiff_t i;
202 es.eigenvalues().real().maxCoeff(&i);
203 const Eigen::Matrix<Scalar, 4, 1> qmat = es.eigenvectors().col(i).real();
204 const Eigen::Matrix<Scalar, 4, 1> smat = -(0.5f / float(npts)) * C2 * qmat;
205
206 const Eigen::Quaternion<Scalar> q(qmat(3), qmat(0), qmat(1), qmat(2));
207 const Eigen::Quaternion<Scalar> s(smat(3), smat(0), smat(1), smat(2));
208
209 const Eigen::Quaternion<Scalar> t = s * q.conjugate();
210
211 const Eigen::Matrix<Scalar, 3, 3> R(q.toRotationMatrix());
212
213 for (int i = 0; i < 3; ++i)
214 for (int j = 0; j < 3; ++j)
215 transformation_matrix(i, j) = R(i, j);
216
217 transformation_matrix(0, 3) = -t.x();
218 transformation_matrix(1, 3) = -t.y();
219 transformation_matrix(2, 3) = -t.z();
220}
221
222} // namespace registration
223} // namespace pcl
224
225#endif /* PCL_REGISTRATION_TRANSFORMATION_ESTIMATION_DQ_HPP_ */
Iterator class for point clouds with or without given indices.
std::size_t size() const
Size of the range the iterator is going through.
PointCloud represents the base class in PCL for storing collections of 3D points.
std::size_t size() const
typename TransformationEstimation< PointSource, PointTarget, Scalar >::Matrix4 Matrix4
void estimateRigidTransformation(const pcl::PointCloud< PointSource > &cloud_src, const pcl::PointCloud< PointTarget > &cloud_tgt, Matrix4 &transformation_matrix) const
Estimate a rigid rotation transformation between a source and a target point cloud using dual quatern...
std::vector< pcl::Correspondence, Eigen::aligned_allocator< pcl::Correspondence > > Correspondences
IndicesAllocator<> Indices
Type used for indices in PCL.
Definition types.h:133
#define PCL_DEPRECATED_HEADER(Major, Minor, Message)
macro for compatibility across compilers and help remove old deprecated headers for the Major....
Definition pcl_macros.h:176