Point Cloud Library (PCL) 1.13.1
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sac_model_stick.hpp
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37 * $Id: sac_model_line.hpp 2328 2011-08-31 08:11:00Z rusu $
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40
41#ifndef PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_STICK_H_
42#define PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_STICK_H_
43
44#include <pcl/sample_consensus/sac_model_stick.h>
45#include <pcl/common/centroid.h>
46#include <pcl/common/concatenate.h>
47#include <pcl/common/eigen.h> // for eigen33
48
49//////////////////////////////////////////////////////////////////////////
50template <typename PointT> bool
52{
53 if (samples.size () != sample_size_)
54 {
55 PCL_ERROR ("[pcl::SampleConsensusModelStick::isSampleGood] Wrong number of samples (is %lu, should be %lu)!\n", samples.size (), sample_size_);
56 return (false);
57 }
58 if (
59 ((*input_)[samples[0]].x != (*input_)[samples[1]].x)
60 &&
61 ((*input_)[samples[0]].y != (*input_)[samples[1]].y)
62 &&
63 ((*input_)[samples[0]].z != (*input_)[samples[1]].z))
64 {
65 return (true);
66 }
67
68 return (false);
69}
70
71//////////////////////////////////////////////////////////////////////////
72template <typename PointT> bool
74 const Indices &samples, Eigen::VectorXf &model_coefficients) const
75{
76 // Need 2 samples
77 if (samples.size () != sample_size_)
78 {
79 PCL_ERROR ("[pcl::SampleConsensusModelStick::computeModelCoefficients] Invalid set of samples given (%lu)!\n", samples.size ());
80 return (false);
81 }
82
83 model_coefficients.resize (model_size_);
84 model_coefficients[0] = (*input_)[samples[0]].x;
85 model_coefficients[1] = (*input_)[samples[0]].y;
86 model_coefficients[2] = (*input_)[samples[0]].z;
87
88 model_coefficients[3] = (*input_)[samples[1]].x;
89 model_coefficients[4] = (*input_)[samples[1]].y;
90 model_coefficients[5] = (*input_)[samples[1]].z;
91
92// model_coefficients[3] = (*input_)[samples[1]].x - model_coefficients[0];
93// model_coefficients[4] = (*input_)[samples[1]].y - model_coefficients[1];
94// model_coefficients[5] = (*input_)[samples[1]].z - model_coefficients[2];
95
96// model_coefficients.template segment<3> (3).normalize ();
97 // We don't care about model_coefficients[6] which is the width (radius) of the stick
98
99 PCL_DEBUG ("[pcl::SampleConsensusModelStick::computeModelCoefficients] Model is (%g,%g,%g,%g,%g,%g).\n",
100 model_coefficients[0], model_coefficients[1], model_coefficients[2],
101 model_coefficients[3], model_coefficients[4], model_coefficients[5]);
102 return (true);
103}
104
105//////////////////////////////////////////////////////////////////////////
106template <typename PointT> void
108 const Eigen::VectorXf &model_coefficients, std::vector<double> &distances) const
109{
110 // Needs a valid set of model coefficients
111 if (!isModelValid (model_coefficients))
112 {
113 PCL_ERROR ("[pcl::SampleConsensusModelStick::getDistancesToModel] Given model is invalid!\n");
114 return;
115 }
116
117 float sqr_threshold = static_cast<float> (radius_max_ * radius_max_);
118 distances.resize (indices_->size ());
119
120 // Obtain the line point and direction
121 Eigen::Vector4f line_pt (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
122 Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0.0f);
123 line_dir.normalize ();
124
125 // Iterate through the 3d points and calculate the distances from them to the line
126 for (std::size_t i = 0; i < indices_->size (); ++i)
127 {
128 // Calculate the distance from the point to the line
129 // D = ||(P2-P1) x (P1-P0)|| / ||P2-P1|| = norm (cross (p2-p1, p2-p0)) / norm(p2-p1)
130 float sqr_distance = (line_pt - (*input_)[(*indices_)[i]].getVector4fMap ()).cross3 (line_dir).squaredNorm ();
131
132 if (sqr_distance < sqr_threshold)
133 {
134 // Need to estimate sqrt here to keep MSAC and friends general
135 distances[i] = std::sqrt (sqr_distance);
136 }
137 else
138 {
139 // Penalize outliers by doubling the distance
140 distances[i] = 2 * std::sqrt (sqr_distance);
141 }
142 }
143}
144
145//////////////////////////////////////////////////////////////////////////
146template <typename PointT> void
148 const Eigen::VectorXf &model_coefficients, const double threshold, Indices &inliers)
149{
150 // Needs a valid set of model coefficients
151 if (!isModelValid (model_coefficients))
152 {
153 PCL_ERROR ("[pcl::SampleConsensusModelStick::selectWithinDistance] Given model is invalid!\n");
154 return;
155 }
156
157 float sqr_threshold = static_cast<float> (threshold * threshold);
158
159 inliers.clear ();
160 error_sqr_dists_.clear ();
161 inliers.reserve (indices_->size ());
162 error_sqr_dists_.reserve (indices_->size ());
163
164 // Obtain the line point and direction
165 Eigen::Vector4f line_pt1 (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
166 Eigen::Vector4f line_pt2 (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0.0f);
167 Eigen::Vector4f line_dir = line_pt2 - line_pt1;
168 //Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0);
169 //Eigen::Vector4f line_dir (model_coefficients[3] - model_coefficients[0], model_coefficients[4] - model_coefficients[1], model_coefficients[5] - model_coefficients[2], 0);
170 line_dir.normalize ();
171 //float norm = line_dir.squaredNorm ();
172
173 // Iterate through the 3d points and calculate the distances from them to the line
174 for (std::size_t i = 0; i < indices_->size (); ++i)
175 {
176 // Calculate the distance from the point to the line
177 // D = ||(P2-P1) x (P1-P0)|| / ||P2-P1|| = norm (cross (p2-p1, p2-p0)) / norm(p2-p1)
178 Eigen::Vector4f dir = (*input_)[(*indices_)[i]].getVector4fMap () - line_pt1;
179 //float u = dir.dot (line_dir);
180
181 // If the point falls outside of the segment, ignore it
182 //if (u < 0.0f || u > 1.0f)
183 // continue;
184
185 float sqr_distance = dir.cross3 (line_dir).squaredNorm ();
186 if (sqr_distance < sqr_threshold)
187 {
188 // Returns the indices of the points whose squared distances are smaller than the threshold
189 inliers.push_back ((*indices_)[i]);
190 error_sqr_dists_.push_back (static_cast<double> (sqr_distance));
191 }
192 }
193}
194
195///////////////////////////////////////////////////////////////////////////
196template <typename PointT> std::size_t
198 const Eigen::VectorXf &model_coefficients, const double threshold) const
199{
200 // Needs a valid set of model coefficients
201 if (!isModelValid (model_coefficients))
202 {
203 PCL_ERROR ("[pcl::SampleConsensusModelStick::countWithinDistance] Given model is invalid!\n");
204 return (0);
205 }
206
207 float sqr_threshold = static_cast<float> (threshold * threshold);
208
209 std::size_t nr_i = 0, nr_o = 0;
210
211 // Obtain the line point and direction
212 Eigen::Vector4f line_pt1 (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
213 Eigen::Vector4f line_pt2 (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0.0f);
214 Eigen::Vector4f line_dir = line_pt2 - line_pt1;
215 line_dir.normalize ();
216
217 //Eigen::Vector4f line_dir (model_coefficients[3] - model_coefficients[0], model_coefficients[4] - model_coefficients[1], model_coefficients[5] - model_coefficients[2], 0);
218 //Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0);
219
220 // Iterate through the 3d points and calculate the distances from them to the line
221 for (std::size_t i = 0; i < indices_->size (); ++i)
222 {
223 // Calculate the distance from the point to the line
224 // D = ||(P2-P1) x (P1-P0)|| / ||P2-P1|| = norm (cross (p2-p1, p2-p0)) / norm(p2-p1)
225 Eigen::Vector4f dir = (*input_)[(*indices_)[i]].getVector4fMap () - line_pt1;
226 //float u = dir.dot (line_dir);
227
228 // If the point falls outside of the segment, ignore it
229 //if (u < 0.0f || u > 1.0f)
230 // continue;
231
232 float sqr_distance = dir.cross3 (line_dir).squaredNorm ();
233 // Use a larger threshold (4 times the radius) to get more points in
234 if (sqr_distance < sqr_threshold)
235 {
236 nr_i++;
237 }
238 else if (sqr_distance < 4.0f * sqr_threshold)
239 {
240 nr_o++;
241 }
242 }
243
244 return (nr_i <= nr_o ? 0 : nr_i - nr_o);
245}
246
247//////////////////////////////////////////////////////////////////////////
248template <typename PointT> void
250 const Indices &inliers, const Eigen::VectorXf &model_coefficients, Eigen::VectorXf &optimized_coefficients) const
251{
252 // Needs a valid set of model coefficients
253 if (!isModelValid (model_coefficients))
254 {
255 optimized_coefficients = model_coefficients;
256 return;
257 }
258
259 // Need more than the minimum sample size to make a difference
260 if (inliers.size () <= sample_size_)
261 {
262 PCL_ERROR ("[pcl::SampleConsensusModelStick::optimizeModelCoefficients] Not enough inliers to refine/optimize the model's coefficients (%lu)! Returning the same coefficients.\n", inliers.size ());
263 optimized_coefficients = model_coefficients;
264 return;
265 }
266
267 optimized_coefficients.resize (model_size_);
268
269 // Compute the 3x3 covariance matrix
270 Eigen::Vector4f centroid;
271 Eigen::Matrix3f covariance_matrix;
272
273 if (0 == computeMeanAndCovarianceMatrix (*input_, inliers, covariance_matrix, centroid))
274 {
275 PCL_ERROR ("[pcl::SampleConsensusModelStick::optimizeModelCoefficients] computeMeanAndCovarianceMatrix failed (returned 0) because there are no valid inliers.\n");
276 optimized_coefficients = model_coefficients;
277 return;
278 }
279
280 optimized_coefficients[0] = centroid[0];
281 optimized_coefficients[1] = centroid[1];
282 optimized_coefficients[2] = centroid[2];
283
284 // Extract the eigenvalues and eigenvectors
285 Eigen::Vector3f eigen_values;
286 Eigen::Vector3f eigen_vector;
287 pcl::eigen33 (covariance_matrix, eigen_values);
288 pcl::computeCorrespondingEigenVector (covariance_matrix, eigen_values [2], eigen_vector);
289
290 optimized_coefficients.template segment<3> (3).matrix () = eigen_vector;
291}
292
293//////////////////////////////////////////////////////////////////////////
294template <typename PointT> void
296 const Indices &inliers, const Eigen::VectorXf &model_coefficients, PointCloud &projected_points, bool copy_data_fields) const
297{
298 // Needs a valid model coefficients
299 if (!isModelValid (model_coefficients))
300 {
301 PCL_ERROR ("[pcl::SampleConsensusModelStick::projectPoints] Given model is invalid!\n");
302 return;
303 }
304
305 // Obtain the line point and direction
306 Eigen::Vector4f line_pt (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
307 Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0.0f);
308
309 projected_points.header = input_->header;
310 projected_points.is_dense = input_->is_dense;
311
312 // Copy all the data fields from the input cloud to the projected one?
313 if (copy_data_fields)
314 {
315 // Allocate enough space and copy the basics
316 projected_points.resize (input_->size ());
317 projected_points.width = input_->width;
318 projected_points.height = input_->height;
319
320 using FieldList = typename pcl::traits::fieldList<PointT>::type;
321 // Iterate over each point
322 for (std::size_t i = 0; i < projected_points.size (); ++i)
323 {
324 // Iterate over each dimension
325 pcl::for_each_type <FieldList> (NdConcatenateFunctor <PointT, PointT> ((*input_)[i], projected_points[i]));
326 }
327
328 // Iterate through the 3d points and calculate the distances from them to the line
329 for (const auto &inlier : inliers)
330 {
331 Eigen::Vector4f pt ((*input_)[inlier].x, (*input_)[inlier].y, (*input_)[inlier].z, 0.0f);
332 // double k = (DOT_PROD_3D (points[i], p21) - dotA_B) / dotB_B;
333 float k = (pt.dot (line_dir) - line_pt.dot (line_dir)) / line_dir.dot (line_dir);
334
335 Eigen::Vector4f pp = line_pt + k * line_dir;
336 // Calculate the projection of the point on the line (pointProj = A + k * B)
337 projected_points[inlier].x = pp[0];
338 projected_points[inlier].y = pp[1];
339 projected_points[inlier].z = pp[2];
340 }
341 }
342 else
343 {
344 // Allocate enough space and copy the basics
345 projected_points.resize (inliers.size ());
346 projected_points.width = inliers.size ();
347 projected_points.height = 1;
348
349 using FieldList = typename pcl::traits::fieldList<PointT>::type;
350 // Iterate over each point
351 for (std::size_t i = 0; i < inliers.size (); ++i)
352 {
353 // Iterate over each dimension
354 pcl::for_each_type <FieldList> (NdConcatenateFunctor <PointT, PointT> ((*input_)[inliers[i]], projected_points[i]));
355 }
356
357 // Iterate through the 3d points and calculate the distances from them to the line
358 for (std::size_t i = 0; i < inliers.size (); ++i)
359 {
360 Eigen::Vector4f pt ((*input_)[inliers[i]].x, (*input_)[inliers[i]].y, (*input_)[inliers[i]].z, 0.0f);
361 // double k = (DOT_PROD_3D (points[i], p21) - dotA_B) / dotB_B;
362 float k = (pt.dot (line_dir) - line_pt.dot (line_dir)) / line_dir.dot (line_dir);
363
364 Eigen::Vector4f pp = line_pt + k * line_dir;
365 // Calculate the projection of the point on the line (pointProj = A + k * B)
366 projected_points[i].x = pp[0];
367 projected_points[i].y = pp[1];
368 projected_points[i].z = pp[2];
369 }
370 }
371}
372
373//////////////////////////////////////////////////////////////////////////
374template <typename PointT> bool
376 const std::set<index_t> &indices, const Eigen::VectorXf &model_coefficients, const double threshold) const
377{
378 // Needs a valid set of model coefficients
379 if (!isModelValid (model_coefficients))
380 {
381 PCL_ERROR ("[pcl::SampleConsensusModelStick::doSamplesVerifyModel] Given model is invalid!\n");
382 return (false);
383 }
384
385 // Obtain the line point and direction
386 Eigen::Vector4f line_pt (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
387 Eigen::Vector4f line_dir (model_coefficients[3] - model_coefficients[0], model_coefficients[4] - model_coefficients[1], model_coefficients[5] - model_coefficients[2], 0.0f);
388 //Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0);
389 line_dir.normalize ();
390
391 float sqr_threshold = static_cast<float> (threshold * threshold);
392 // Iterate through the 3d points and calculate the distances from them to the line
393 for (const auto &index : indices)
394 {
395 // Calculate the distance from the point to the line
396 // D = ||(P2-P1) x (P1-P0)|| / ||P2-P1|| = norm (cross (p2-p1, p2-p0)) / norm(p2-p1)
397 if ((line_pt - (*input_)[index].getVector4fMap ()).cross3 (line_dir).squaredNorm () > sqr_threshold)
398 {
399 return (false);
400 }
401 }
402
403 return (true);
404}
405
406#define PCL_INSTANTIATE_SampleConsensusModelStick(T) template class PCL_EXPORTS pcl::SampleConsensusModelStick<T>;
407
408#endif // PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_STICK_H_
409
Define methods for centroid estimation and covariance matrix calculus.
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.
bool doSamplesVerifyModel(const std::set< index_t > &indices, const Eigen::VectorXf &model_coefficients, const double threshold) const override
Verify whether a subset of indices verifies the given stick model coefficients.
bool computeModelCoefficients(const Indices &samples, Eigen::VectorXf &model_coefficients) const override
Check whether the given index samples can form a valid stick model, compute the model coefficients fr...
void getDistancesToModel(const Eigen::VectorXf &model_coefficients, std::vector< double > &distances) const override
Compute all squared distances from the cloud data to a given stick model.
typename SampleConsensusModel< PointT >::PointCloud PointCloud
bool isSampleGood(const Indices &samples) const override
Check if a sample of indices results in a good sample of points indices.
void projectPoints(const Indices &inliers, const Eigen::VectorXf &model_coefficients, PointCloud &projected_points, bool copy_data_fields=true) const override
Create a new point cloud with inliers projected onto the stick model.
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.
void optimizeModelCoefficients(const Indices &inliers, const Eigen::VectorXf &model_coefficients, Eigen::VectorXf &optimized_coefficients) const override
Recompute the stick coefficients using the given inlier set and return them to the user.
void computeCorrespondingEigenVector(const Matrix &mat, const typename Matrix::Scalar &eigenvalue, Vector &eigenvector)
determines the corresponding eigenvector to the given eigenvalue of the symmetric positive semi defin...
Definition eigen.hpp:226
unsigned int computeMeanAndCovarianceMatrix(const pcl::PointCloud< PointT > &cloud, Eigen::Matrix< Scalar, 3, 3 > &covariance_matrix, Eigen::Matrix< Scalar, 4, 1 > &centroid)
Compute the normalized 3x3 covariance matrix and the centroid of a given set of points in a single lo...
Definition centroid.hpp:508
void eigen33(const Matrix &mat, typename Matrix::Scalar &eigenvalue, Vector &eigenvector)
determines the eigenvector and eigenvalue of the smallest eigenvalue of the symmetric positive semi d...
Definition eigen.hpp:295
IndicesAllocator<> Indices
Type used for indices in PCL.
Definition types.h:133