54 Eigen::Vector4f pt(0.0f, 0.0f, 0.0f, 1.0f), pt_t;
55 Eigen::Matrix4f tr = transform.template cast<float>();
59 if (source_has_normals_) {
60 Eigen::Vector3f nt, nt_t;
61 Eigen::Matrix3f rot = tr.block<3, 3>(0, 0);
63 for (std::size_t i = 0; i < input.size(); ++i) {
64 const auto* data_in =
reinterpret_cast<const std::uint8_t*
>(&input[i]);
65 auto* data_out =
reinterpret_cast<std::uint8_t*
>(&output[i]);
66 memcpy(&pt[0], data_in + x_idx_offset_,
sizeof(
float));
67 memcpy(&pt[1], data_in + y_idx_offset_,
sizeof(
float));
68 memcpy(&pt[2], data_in + z_idx_offset_,
sizeof(
float));
70 if (!std::isfinite(pt[0]) || !std::isfinite(pt[1]) || !std::isfinite(pt[2]))
75 memcpy(data_out + x_idx_offset_, &pt_t[0],
sizeof(
float));
76 memcpy(data_out + y_idx_offset_, &pt_t[1],
sizeof(
float));
77 memcpy(data_out + z_idx_offset_, &pt_t[2],
sizeof(
float));
79 memcpy(&nt[0], data_in + nx_idx_offset_,
sizeof(
float));
80 memcpy(&nt[1], data_in + ny_idx_offset_,
sizeof(
float));
81 memcpy(&nt[2], data_in + nz_idx_offset_,
sizeof(
float));
83 if (!std::isfinite(nt[0]) || !std::isfinite(nt[1]) || !std::isfinite(nt[2]))
88 memcpy(data_out + nx_idx_offset_, &nt_t[0],
sizeof(
float));
89 memcpy(data_out + ny_idx_offset_, &nt_t[1],
sizeof(
float));
90 memcpy(data_out + nz_idx_offset_, &nt_t[2],
sizeof(
float));
94 for (std::size_t i = 0; i < input.size(); ++i) {
95 const auto* data_in =
reinterpret_cast<const std::uint8_t*
>(&input[i]);
96 auto* data_out =
reinterpret_cast<std::uint8_t*
>(&output[i]);
97 memcpy(&pt[0], data_in + x_idx_offset_,
sizeof(
float));
98 memcpy(&pt[1], data_in + y_idx_offset_,
sizeof(
float));
99 memcpy(&pt[2], data_in + z_idx_offset_,
sizeof(
float));
101 if (!std::isfinite(pt[0]) || !std::isfinite(pt[1]) || !std::isfinite(pt[2]))
106 memcpy(data_out + x_idx_offset_, &pt_t[0],
sizeof(
float));
107 memcpy(data_out + y_idx_offset_, &pt_t[1],
sizeof(
float));
108 memcpy(data_out + z_idx_offset_, &pt_t[2],
sizeof(
float));
125 final_transformation_ = guess;
128 if (guess != Matrix4::Identity()) {
129 input_transformed->resize(input_->size());
131 transformCloud(*input_, *input_transformed, guess);
134 *input_transformed = *input_;
136 transformation_ = Matrix4::Identity();
139 determineRequiredBlobData();
141 if (need_target_blob_)
145 correspondence_estimation_->setInputTarget(target_);
146 if (correspondence_estimation_->requiresTargetNormals())
147 correspondence_estimation_->setTargetNormals(target_blob);
149 for (std::size_t i = 0; i < correspondence_rejectors_.size(); ++i) {
151 if (rej->requiresTargetPoints())
152 rej->setTargetPoints(target_blob);
153 if (rej->requiresTargetNormals() && target_has_normals_)
154 rej->setTargetNormals(target_blob);
157 convergence_criteria_->setMaximumIterations(max_iterations_);
158 convergence_criteria_->setRelativeMSE(euclidean_fitness_epsilon_);
159 convergence_criteria_->setTranslationThreshold(transformation_epsilon_);
160 if (transformation_rotation_epsilon_ > 0)
161 convergence_criteria_->setRotationThreshold(transformation_rotation_epsilon_);
163 convergence_criteria_->setRotationThreshold(1.0 - transformation_epsilon_);
169 if (need_source_blob_) {
174 previous_transformation_ = transformation_;
177 correspondence_estimation_->setInputSource(input_transformed);
178 if (correspondence_estimation_->requiresSourceNormals())
179 correspondence_estimation_->setSourceNormals(input_transformed_blob);
181 if (use_reciprocal_correspondence_)
182 correspondence_estimation_->determineReciprocalCorrespondences(
183 *correspondences_, corr_dist_threshold_);
185 correspondence_estimation_->determineCorrespondences(*correspondences_,
186 corr_dist_threshold_);
190 for (std::size_t i = 0; i < correspondence_rejectors_.size(); ++i) {
192 PCL_DEBUG(
"Applying a correspondence rejector method: %s.\n",
193 rej->getClassName().c_str());
194 if (rej->requiresSourcePoints())
195 rej->setSourcePoints(input_transformed_blob);
196 if (rej->requiresSourceNormals() && source_has_normals_)
197 rej->setSourceNormals(input_transformed_blob);
198 rej->setInputCorrespondences(temp_correspondences);
199 rej->getCorrespondences(*correspondences_);
201 if (i < correspondence_rejectors_.size() - 1)
202 *temp_correspondences = *correspondences_;
206 if (correspondences_->size() < min_number_correspondences_) {
207 PCL_ERROR(
"[pcl::%s::computeTransformation] Not enough correspondences found. "
208 "Relax your threshold parameters.\n",
209 getClassName().c_str());
210 convergence_criteria_->setConvergenceState(
212 Scalar>::CONVERGENCE_CRITERIA_NO_CORRESPONDENCES);
218 transformation_estimation_->estimateRigidTransformation(
219 *input_transformed, *target_, *correspondences_, transformation_);
222 transformCloud(*input_transformed, *input_transformed, transformation_);
225 final_transformation_ = transformation_ * final_transformation_;
230 if (update_visualizer_ !=
nullptr) {
233 source_indices_good.emplace_back(corr.index_query);
234 target_indices_good.emplace_back(corr.index_match);
237 *input_transformed, source_indices_good, *target_, target_indices_good);
240 converged_ =
static_cast<bool>((*convergence_criteria_));
241 }
while (convergence_criteria_->getConvergenceState() ==
243 Scalar>::CONVERGENCE_CRITERIA_NOT_CONVERGED);
246 PCL_DEBUG(
"Transformation "
247 "is:\n\t%5f\t%5f\t%5f\t%5f\n\t%5f\t%5f\t%5f\t%5f\n\t%5f\t%5f\t%5f\t%5f\n\t%"
248 "5f\t%5f\t%5f\t%5f\n",
249 final_transformation_(0, 0),
250 final_transformation_(0, 1),
251 final_transformation_(0, 2),
252 final_transformation_(0, 3),
253 final_transformation_(1, 0),
254 final_transformation_(1, 1),
255 final_transformation_(1, 2),
256 final_transformation_(1, 3),
257 final_transformation_(2, 0),
258 final_transformation_(2, 1),
259 final_transformation_(2, 2),
260 final_transformation_(2, 3),
261 final_transformation_(3, 0),
262 final_transformation_(3, 1),
263 final_transformation_(3, 2),
264 final_transformation_(3, 3));
269 transformCloud(*input_, output, final_transformation_);