Point Cloud Library (PCL) 1.13.1
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sac_model_registration.hpp
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40
41#ifndef PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_REGISTRATION_H_
42#define PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_REGISTRATION_H_
43
44#include <pcl/sample_consensus/sac_model_registration.h>
45
46//////////////////////////////////////////////////////////////////////////
47template <typename PointT> bool
49{
50 if (samples.size () != sample_size_)
51 {
52 PCL_ERROR ("[pcl::SampleConsensusModelRegistration::isSampleGood] Wrong number of samples (is %lu, should be %lu)!\n", samples.size (), sample_size_);
53 return (false);
54 }
55 using namespace pcl::common;
56 using namespace pcl::traits;
57
58 PointT p10 = (*input_)[samples[1]] - (*input_)[samples[0]];
59 PointT p20 = (*input_)[samples[2]] - (*input_)[samples[0]];
60 PointT p21 = (*input_)[samples[2]] - (*input_)[samples[1]];
61
62 return ((p10.x * p10.x + p10.y * p10.y + p10.z * p10.z) > sample_dist_thresh_ &&
63 (p20.x * p20.x + p20.y * p20.y + p20.z * p20.z) > sample_dist_thresh_ &&
64 (p21.x * p21.x + p21.y * p21.y + p21.z * p21.z) > sample_dist_thresh_);
65}
66
67//////////////////////////////////////////////////////////////////////////
68template <typename PointT> bool
69pcl::SampleConsensusModelRegistration<PointT>::computeModelCoefficients (const Indices &samples, Eigen::VectorXf &model_coefficients) const
70{
71 if (!target_)
72 {
73 PCL_ERROR ("[pcl::SampleConsensusModelRegistration::computeModelCoefficients] No target dataset given!\n");
74 return (false);
75 }
76 // Need 3 samples
77 if (samples.size () != sample_size_)
78 {
79 return (false);
80 }
81
82 Indices indices_tgt (3);
83 for (int i = 0; i < 3; ++i)
84 {
85 const auto it = correspondences_.find (samples[i]);
86 if (it == correspondences_.cend ())
87 {
88 PCL_ERROR ("[pcl::SampleConsensusModelRegistration::computeModelCoefficients] Element with key %i is not in map (map contains %lu elements).\n",
89 samples[i], correspondences_.size ());
90 return (false);
91 }
92 indices_tgt[i] = it->second;
93 }
94
95 estimateRigidTransformationSVD (*input_, samples, *target_, indices_tgt, model_coefficients);
96 return (true);
97}
98
99//////////////////////////////////////////////////////////////////////////
100template <typename PointT> void
101pcl::SampleConsensusModelRegistration<PointT>::getDistancesToModel (const Eigen::VectorXf &model_coefficients, std::vector<double> &distances) const
102{
103 if (indices_->size () != indices_tgt_->size ())
104 {
105 PCL_ERROR ("[pcl::SampleConsensusModelRegistration::getDistancesToModel] Number of source indices (%lu) differs than number of target indices (%lu)!\n", indices_->size (), indices_tgt_->size ());
106 distances.clear ();
107 return;
108 }
109 if (!target_)
110 {
111 PCL_ERROR ("[pcl::SampleConsensusModelRegistration::getDistanceToModel] No target dataset given!\n");
112 return;
113 }
114 // Check if the model is valid given the user constraints
115 if (!isModelValid (model_coefficients))
116 {
117 distances.clear ();
118 return;
119 }
120 distances.resize (indices_->size ());
121
122 // Get the 4x4 transformation
123 Eigen::Matrix4f transform;
124 transform.row (0).matrix () = model_coefficients.segment<4>(0);
125 transform.row (1).matrix () = model_coefficients.segment<4>(4);
126 transform.row (2).matrix () = model_coefficients.segment<4>(8);
127 transform.row (3).matrix () = model_coefficients.segment<4>(12);
128
129 for (std::size_t i = 0; i < indices_->size (); ++i)
130 {
131 Eigen::Vector4f pt_src ((*input_)[(*indices_)[i]].x,
132 (*input_)[(*indices_)[i]].y,
133 (*input_)[(*indices_)[i]].z, 1.0f);
134 Eigen::Vector4f pt_tgt ((*target_)[(*indices_tgt_)[i]].x,
135 (*target_)[(*indices_tgt_)[i]].y,
136 (*target_)[(*indices_tgt_)[i]].z, 1.0f);
137
138 Eigen::Vector4f p_tr (transform * pt_src);
139 // Calculate the distance from the transformed point to its correspondence
140 // need to compute the real norm here to keep MSAC and friends general
141 distances[i] = (p_tr - pt_tgt).norm ();
142 }
143}
144
145//////////////////////////////////////////////////////////////////////////
146template <typename PointT> void
147pcl::SampleConsensusModelRegistration<PointT>::selectWithinDistance (const Eigen::VectorXf &model_coefficients, const double threshold, Indices &inliers)
148{
149 if (indices_->size () != indices_tgt_->size ())
150 {
151 PCL_ERROR ("[pcl::SampleConsensusModelRegistration::selectWithinDistance] Number of source indices (%lu) differs than number of target indices (%lu)!\n", indices_->size (), indices_tgt_->size ());
152 inliers.clear ();
153 return;
154 }
155 if (!target_)
156 {
157 PCL_ERROR ("[pcl::SampleConsensusModelRegistration::selectWithinDistance] No target dataset given!\n");
158 return;
159 }
160
161 double thresh = threshold * threshold;
162
163 // Check if the model is valid given the user constraints
164 if (!isModelValid (model_coefficients))
165 {
166 inliers.clear ();
167 return;
168 }
169
170 inliers.clear ();
171 error_sqr_dists_.clear ();
172 inliers.reserve (indices_->size ());
173 error_sqr_dists_.reserve (indices_->size ());
174
175 Eigen::Matrix4f transform;
176 transform.row (0).matrix () = model_coefficients.segment<4>(0);
177 transform.row (1).matrix () = model_coefficients.segment<4>(4);
178 transform.row (2).matrix () = model_coefficients.segment<4>(8);
179 transform.row (3).matrix () = model_coefficients.segment<4>(12);
180
181 for (std::size_t i = 0; i < indices_->size (); ++i)
182 {
183 Eigen::Vector4f pt_src ((*input_)[(*indices_)[i]].x,
184 (*input_)[(*indices_)[i]].y,
185 (*input_)[(*indices_)[i]].z, 1);
186 Eigen::Vector4f pt_tgt ((*target_)[(*indices_tgt_)[i]].x,
187 (*target_)[(*indices_tgt_)[i]].y,
188 (*target_)[(*indices_tgt_)[i]].z, 1);
189
190 Eigen::Vector4f p_tr (transform * pt_src);
191
192 float distance = (p_tr - pt_tgt).squaredNorm ();
193 // Calculate the distance from the transformed point to its correspondence
194 if (distance < thresh)
195 {
196 inliers.push_back ((*indices_)[i]);
197 error_sqr_dists_.push_back (static_cast<double> (distance));
198 }
199 }
200}
201
202//////////////////////////////////////////////////////////////////////////
203template <typename PointT> std::size_t
205 const Eigen::VectorXf &model_coefficients, const double threshold) const
206{
207 if (indices_->size () != indices_tgt_->size ())
208 {
209 PCL_ERROR ("[pcl::SampleConsensusModelRegistration::countWithinDistance] Number of source indices (%lu) differs than number of target indices (%lu)!\n", indices_->size (), indices_tgt_->size ());
210 return (0);
211 }
212 if (!target_)
213 {
214 PCL_ERROR ("[pcl::SampleConsensusModelRegistration::countWithinDistance] No target dataset given!\n");
215 return (0);
216 }
217
218 double thresh = threshold * threshold;
219
220 // Check if the model is valid given the user constraints
221 if (!isModelValid (model_coefficients))
222 {
223 return (0);
224 }
225
226 Eigen::Matrix4f transform;
227 transform.row (0).matrix () = model_coefficients.segment<4>(0);
228 transform.row (1).matrix () = model_coefficients.segment<4>(4);
229 transform.row (2).matrix () = model_coefficients.segment<4>(8);
230 transform.row (3).matrix () = model_coefficients.segment<4>(12);
231
232 std::size_t nr_p = 0;
233 for (std::size_t i = 0; i < indices_->size (); ++i)
234 {
235 Eigen::Vector4f pt_src ((*input_)[(*indices_)[i]].x,
236 (*input_)[(*indices_)[i]].y,
237 (*input_)[(*indices_)[i]].z, 1);
238 Eigen::Vector4f pt_tgt ((*target_)[(*indices_tgt_)[i]].x,
239 (*target_)[(*indices_tgt_)[i]].y,
240 (*target_)[(*indices_tgt_)[i]].z, 1);
241
242 Eigen::Vector4f p_tr (transform * pt_src);
243 // Calculate the distance from the transformed point to its correspondence
244 if ((p_tr - pt_tgt).squaredNorm () < thresh)
245 nr_p++;
246 }
247 PCL_DEBUG ("[pcl::SampleConsensusModelRegistration::countWithinDistance] %zu inliers of %zu total points, threshold=%g\n", nr_p, indices_->size(), threshold);
248 return (nr_p);
249}
250
251//////////////////////////////////////////////////////////////////////////
252template <typename PointT> void
253pcl::SampleConsensusModelRegistration<PointT>::optimizeModelCoefficients (const Indices &inliers, const Eigen::VectorXf &model_coefficients, Eigen::VectorXf &optimized_coefficients) const
254{
255 if (indices_->size () != indices_tgt_->size ())
256 {
257 PCL_ERROR ("[pcl::SampleConsensusModelRegistration::optimizeModelCoefficients] Number of source indices (%lu) differs than number of target indices (%lu)!\n", indices_->size (), indices_tgt_->size ());
258 optimized_coefficients = model_coefficients;
259 return;
260 }
261
262 // Check if the model is valid given the user constraints
263 if (!isModelValid (model_coefficients) || !target_)
264 {
265 optimized_coefficients = model_coefficients;
266 return;
267 }
268
269 Indices indices_src (inliers.size ());
270 Indices indices_tgt (inliers.size ());
271 for (std::size_t i = 0; i < inliers.size (); ++i)
272 {
273 indices_src[i] = inliers[i];
274 const auto it = correspondences_.find (indices_src[i]);
275 if (it == correspondences_.cend ())
276 {
277 PCL_ERROR ("[pcl::SampleConsensusModelRegistration::optimizeModelCoefficients] Element with key %i is not in map (map contains %lu elements).\n",
278 indices_src[i], correspondences_.size ());
279 optimized_coefficients = model_coefficients;
280 return;
281 }
282 indices_tgt[i] = it->second;
283 }
284
285 estimateRigidTransformationSVD (*input_, indices_src, *target_, indices_tgt, optimized_coefficients);
286}
287
288//////////////////////////////////////////////////////////////////////////
289template <typename PointT> void
291 const pcl::PointCloud<PointT> &cloud_src,
292 const Indices &indices_src,
293 const pcl::PointCloud<PointT> &cloud_tgt,
294 const Indices &indices_tgt,
295 Eigen::VectorXf &transform) const
296{
297 transform.resize (16);
298
299 Eigen::Matrix<double, 3, Eigen::Dynamic> src (3, indices_src.size ());
300 Eigen::Matrix<double, 3, Eigen::Dynamic> tgt (3, indices_tgt.size ());
301
302 for (std::size_t i = 0; i < indices_src.size (); ++i)
303 {
304 src (0, i) = cloud_src[indices_src[i]].x;
305 src (1, i) = cloud_src[indices_src[i]].y;
306 src (2, i) = cloud_src[indices_src[i]].z;
307
308 tgt (0, i) = cloud_tgt[indices_tgt[i]].x;
309 tgt (1, i) = cloud_tgt[indices_tgt[i]].y;
310 tgt (2, i) = cloud_tgt[indices_tgt[i]].z;
311 }
312
313 // Call Umeyama directly from Eigen
314 PCL_DEBUG_STREAM("[pcl::SampleConsensusModelRegistration::estimateRigidTransformationSVD] src and tgt:" << std::endl << src << std::endl << std::endl << tgt << std::endl);
315 Eigen::Matrix4d transformation_matrix = pcl::umeyama (src, tgt, false);
316
317 // Return the correct transformation
318 transform.segment<4> (0).matrix () = transformation_matrix.cast<float> ().row (0);
319 transform.segment<4> (4).matrix () = transformation_matrix.cast<float> ().row (1);
320 transform.segment<4> (8).matrix () = transformation_matrix.cast<float> ().row (2);
321 transform.segment<4> (12).matrix () = transformation_matrix.cast<float> ().row (3);
322}
323
324#define PCL_INSTANTIATE_SampleConsensusModelRegistration(T) template class PCL_EXPORTS pcl::SampleConsensusModelRegistration<T>;
325
326#endif // PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_REGISTRATION_H_
327
PointCloud represents the base class in PCL for storing collections of 3D points.
std::size_t countWithinDistance(const Eigen::VectorXf &model_coefficients, const double threshold) const override
Count all the points which respect the given model coefficients as inliers.
bool computeModelCoefficients(const Indices &samples, Eigen::VectorXf &model_coefficients) const override
Compute a 4x4 rigid transformation matrix from the samples given.
void getDistancesToModel(const Eigen::VectorXf &model_coefficients, std::vector< double > &distances) const override
Compute all distances from the transformed points to their correspondences.
void estimateRigidTransformationSVD(const pcl::PointCloud< PointT > &cloud_src, const Indices &indices_src, const pcl::PointCloud< PointT > &cloud_tgt, const Indices &indices_tgt, Eigen::VectorXf &transform) const
Estimate a rigid transformation between a source and a target point cloud using an SVD closed-form so...
bool isSampleGood(const Indices &samples) const override
Check if a sample of indices results in a good sample of points indices.
void optimizeModelCoefficients(const Indices &inliers, const Eigen::VectorXf &model_coefficients, Eigen::VectorXf &optimized_coefficients) const override
Recompute the 4x4 transformation using the given inlier set.
void selectWithinDistance(const Eigen::VectorXf &model_coefficients, const double threshold, Indices &inliers) override
Select all the points which respect the given model coefficients as inliers.
Eigen::internal::umeyama_transform_matrix_type< Derived, OtherDerived >::type umeyama(const Eigen::MatrixBase< Derived > &src, const Eigen::MatrixBase< OtherDerived > &dst, bool with_scaling=false)
Returns the transformation between two point sets.
Definition eigen.hpp:659
IndicesAllocator<> Indices
Type used for indices in PCL.
Definition types.h:133
A point structure representing Euclidean xyz coordinates, and the RGB color.