Point Cloud Library (PCL)  1.11.1-dev
sac_model_stick.hpp
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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 //////////////////////////////////////////////////////////////////////////
50 template <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 //////////////////////////////////////////////////////////////////////////
72 template <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 //////////////////////////////////////////////////////////////////////////
106 template <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] = sqrt (sqr_distance);
136  }
137  else
138  {
139  // Penalize outliers by doubling the distance
140  distances[i] = 2 * sqrt (sqr_distance);
141  }
142  }
143 }
144 
145 //////////////////////////////////////////////////////////////////////////
146 template <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 ///////////////////////////////////////////////////////////////////////////
196 template <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 //////////////////////////////////////////////////////////////////////////
248 template <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  computeMeanAndCovarianceMatrix (*input_, inliers, covariance_matrix, centroid);
274 
275  optimized_coefficients[0] = centroid[0];
276  optimized_coefficients[1] = centroid[1];
277  optimized_coefficients[2] = centroid[2];
278 
279  // Extract the eigenvalues and eigenvectors
280  Eigen::Vector3f eigen_values;
281  Eigen::Vector3f eigen_vector;
282  pcl::eigen33 (covariance_matrix, eigen_values);
283  pcl::computeCorrespondingEigenVector (covariance_matrix, eigen_values [2], eigen_vector);
284 
285  optimized_coefficients.template segment<3> (3).matrix () = eigen_vector;
286 }
287 
288 //////////////////////////////////////////////////////////////////////////
289 template <typename PointT> void
291  const Indices &inliers, const Eigen::VectorXf &model_coefficients, PointCloud &projected_points, bool copy_data_fields) const
292 {
293  // Needs a valid model coefficients
294  if (!isModelValid (model_coefficients))
295  {
296  PCL_ERROR ("[pcl::SampleConsensusModelStick::projectPoints] Given model is invalid!\n");
297  return;
298  }
299 
300  // Obtain the line point and direction
301  Eigen::Vector4f line_pt (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
302  Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0.0f);
303 
304  projected_points.header = input_->header;
305  projected_points.is_dense = input_->is_dense;
306 
307  // Copy all the data fields from the input cloud to the projected one?
308  if (copy_data_fields)
309  {
310  // Allocate enough space and copy the basics
311  projected_points.resize (input_->size ());
312  projected_points.width = input_->width;
313  projected_points.height = input_->height;
314 
315  using FieldList = typename pcl::traits::fieldList<PointT>::type;
316  // Iterate over each point
317  for (std::size_t i = 0; i < projected_points.size (); ++i)
318  {
319  // Iterate over each dimension
320  pcl::for_each_type <FieldList> (NdConcatenateFunctor <PointT, PointT> ((*input_)[i], projected_points[i]));
321  }
322 
323  // Iterate through the 3d points and calculate the distances from them to the line
324  for (const auto &inlier : inliers)
325  {
326  Eigen::Vector4f pt ((*input_)[inlier].x, (*input_)[inlier].y, (*input_)[inlier].z, 0.0f);
327  // double k = (DOT_PROD_3D (points[i], p21) - dotA_B) / dotB_B;
328  float k = (pt.dot (line_dir) - line_pt.dot (line_dir)) / line_dir.dot (line_dir);
329 
330  Eigen::Vector4f pp = line_pt + k * line_dir;
331  // Calculate the projection of the point on the line (pointProj = A + k * B)
332  projected_points[inlier].x = pp[0];
333  projected_points[inlier].y = pp[1];
334  projected_points[inlier].z = pp[2];
335  }
336  }
337  else
338  {
339  // Allocate enough space and copy the basics
340  projected_points.resize (inliers.size ());
341  projected_points.width = inliers.size ();
342  projected_points.height = 1;
343 
344  using FieldList = typename pcl::traits::fieldList<PointT>::type;
345  // Iterate over each point
346  for (std::size_t i = 0; i < inliers.size (); ++i)
347  {
348  // Iterate over each dimension
349  pcl::for_each_type <FieldList> (NdConcatenateFunctor <PointT, PointT> ((*input_)[inliers[i]], projected_points[i]));
350  }
351 
352  // Iterate through the 3d points and calculate the distances from them to the line
353  for (std::size_t i = 0; i < inliers.size (); ++i)
354  {
355  Eigen::Vector4f pt ((*input_)[inliers[i]].x, (*input_)[inliers[i]].y, (*input_)[inliers[i]].z, 0.0f);
356  // double k = (DOT_PROD_3D (points[i], p21) - dotA_B) / dotB_B;
357  float k = (pt.dot (line_dir) - line_pt.dot (line_dir)) / line_dir.dot (line_dir);
358 
359  Eigen::Vector4f pp = line_pt + k * line_dir;
360  // Calculate the projection of the point on the line (pointProj = A + k * B)
361  projected_points[i].x = pp[0];
362  projected_points[i].y = pp[1];
363  projected_points[i].z = pp[2];
364  }
365  }
366 }
367 
368 //////////////////////////////////////////////////////////////////////////
369 template <typename PointT> bool
371  const std::set<index_t> &indices, const Eigen::VectorXf &model_coefficients, const double threshold) const
372 {
373  // Needs a valid set of model coefficients
374  if (!isModelValid (model_coefficients))
375  {
376  PCL_ERROR ("[pcl::SampleConsensusModelStick::doSamplesVerifyModel] Given model is invalid!\n");
377  return (false);
378  }
379 
380  // Obtain the line point and direction
381  Eigen::Vector4f line_pt (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
382  Eigen::Vector4f line_dir (model_coefficients[3] - model_coefficients[0], model_coefficients[4] - model_coefficients[1], model_coefficients[5] - model_coefficients[2], 0.0f);
383  //Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0);
384  line_dir.normalize ();
385 
386  float sqr_threshold = static_cast<float> (threshold * threshold);
387  // Iterate through the 3d points and calculate the distances from them to the line
388  for (const auto &index : indices)
389  {
390  // Calculate the distance from the point to the line
391  // D = ||(P2-P1) x (P1-P0)|| / ||P2-P1|| = norm (cross (p2-p1, p2-p0)) / norm(p2-p1)
392  if ((line_pt - (*input_)[index].getVector4fMap ()).cross3 (line_dir).squaredNorm () > sqr_threshold)
393  {
394  return (false);
395  }
396  }
397 
398  return (true);
399 }
400 
401 #define PCL_INSTANTIATE_SampleConsensusModelStick(T) template class PCL_EXPORTS pcl::SampleConsensusModelStick<T>;
402 
403 #endif // PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_STICK_H_
404 
pcl::computeMeanAndCovarianceMatrix
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:485
pcl::PointCloud::height
std::uint32_t height
The point cloud height (if organized as an image-structure).
Definition: point_cloud.h:394
pcl::SampleConsensusModelStick::selectWithinDistance
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.
Definition: sac_model_stick.hpp:147
pcl::SampleConsensusModelStick::doSamplesVerifyModel
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.
Definition: sac_model_stick.hpp:370
pcl::SampleConsensusModelStick::countWithinDistance
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.
Definition: sac_model_stick.hpp:197
pcl::SampleConsensusModelStick::computeModelCoefficients
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...
Definition: sac_model_stick.hpp:73
pcl::NdConcatenateFunctor
Helper functor structure for concatenate.
Definition: concatenate.h:49
pcl::PointCloud
PointCloud represents the base class in PCL for storing collections of 3D points.
Definition: distances.h:55
pcl::eigen33
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:296
pcl::SampleConsensusModelStick::isSampleGood
bool isSampleGood(const Indices &samples) const override
Check if a sample of indices results in a good sample of points indices.
Definition: sac_model_stick.hpp:51
pcl::PointCloud::width
std::uint32_t width
The point cloud width (if organized as an image-structure).
Definition: point_cloud.h:392
pcl::PointCloud::is_dense
bool is_dense
True if no points are invalid (e.g., have NaN or Inf values in any of their floating point fields).
Definition: point_cloud.h:397
pcl::PointCloud::resize
void resize(std::size_t count)
Resizes the container to contain count elements.
Definition: point_cloud.h:456
pcl::PointCloud::header
pcl::PCLHeader header
The point cloud header.
Definition: point_cloud.h:386
pcl::Indices
IndicesAllocator<> Indices
Type used for indices in PCL.
Definition: types.h:133
pcl::PointCloud::size
std::size_t size() const
Definition: point_cloud.h:437
pcl::computeCorrespondingEigenVector
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
pcl::SampleConsensusModelStick::getDistancesToModel
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.
Definition: sac_model_stick.hpp:107
pcl::SampleConsensusModelStick::projectPoints
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.
Definition: sac_model_stick.hpp:290
centroid.h
pcl::SampleConsensusModelStick::optimizeModelCoefficients
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.
Definition: sac_model_stick.hpp:249