Point Cloud Library (PCL) 1.12.1
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] = 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//////////////////////////////////////////////////////////////////////////
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 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//////////////////////////////////////////////////////////////////////////
289template <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//////////////////////////////////////////////////////////////////////////
369template <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
Define methods for centroid estimation and covariance matrix calculus.
PointCloud represents the base class in PCL for storing collections of 3D points.
Definition: point_cloud.h:173
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:403
void resize(std::size_t count)
Resizes the container to contain count elements.
Definition: point_cloud.h:462
std::uint32_t width
The point cloud width (if organized as an image-structure).
Definition: point_cloud.h:398
pcl::PCLHeader header
The point cloud header.
Definition: point_cloud.h:392
std::uint32_t height
The point cloud height (if organized as an image-structure).
Definition: point_cloud.h:400
std::size_t size() const
Definition: point_cloud.h:443
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.
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:485
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
IndicesAllocator<> Indices
Type used for indices in PCL.
Definition: types.h:133
Helper functor structure for concatenate.
Definition: concatenate.h:50