40 #ifndef PCL_ROPS_ESTIMATION_HPP_
41 #define PCL_ROPS_ESTIMATION_HPP_
43 #include <pcl/features/rops_estimation.h>
47 #include <Eigen/Eigenvalues>
50 template <
typename Po
intInT,
typename Po
intOutT>
53 number_of_rotations_ (3),
54 support_radius_ (1.0f),
55 sqr_support_radius_ (1.0f),
58 triangles_of_the_point_ (0)
63 template <
typename Po
intInT,
typename Po
intOutT>
67 triangles_of_the_point_.clear ();
71 template <
typename Po
intInT,
typename Po
intOutT>
void
74 if (number_of_bins != 0)
75 number_of_bins_ = number_of_bins;
79 template <
typename Po
intInT,
typename Po
intOutT>
unsigned int
82 return (number_of_bins_);
86 template <
typename Po
intInT,
typename Po
intOutT>
void
89 if (number_of_rotations != 0)
91 number_of_rotations_ = number_of_rotations;
92 step_ = 90.0f /
static_cast <float> (number_of_rotations_ + 1);
97 template <
typename Po
intInT,
typename Po
intOutT>
unsigned int
100 return (number_of_rotations_);
104 template <
typename Po
intInT,
typename Po
intOutT>
void
107 if (support_radius > 0.0f)
109 support_radius_ = support_radius;
110 sqr_support_radius_ = support_radius * support_radius;
115 template <
typename Po
intInT,
typename Po
intOutT>
float
118 return (support_radius_);
122 template <
typename Po
intInT,
typename Po
intOutT>
void
125 triangles_ = triangles;
129 template <
typename Po
intInT,
typename Po
intOutT>
void
132 triangles = triangles_;
136 template <
typename Po
intInT,
typename Po
intOutT>
void
139 if (triangles_.empty ())
145 buildListOfPointsTriangles ();
148 unsigned int feature_size = number_of_rotations_ * 3 * 3 * 5;
149 const auto number_of_points = indices_->size ();
151 output.reserve (number_of_points);
153 for (
const auto& idx: *indices_)
155 std::set <unsigned int> local_triangles;
157 getLocalSurface ((*input_)[idx], local_triangles, local_points);
159 Eigen::Matrix3f lrf_matrix;
160 computeLRF ((*input_)[idx], local_triangles, lrf_matrix);
162 PointCloudIn transformed_cloud;
163 transformCloud ((*input_)[idx], lrf_matrix, local_points, transformed_cloud);
165 std::array<PointInT, 3> axes;
166 axes[0].x = 1.0f; axes[0].y = 0.0f; axes[0].z = 0.0f;
167 axes[1].x = 0.0f; axes[1].y = 1.0f; axes[1].z = 0.0f;
168 axes[2].x = 0.0f; axes[2].y = 0.0f; axes[2].z = 1.0f;
169 std::vector <float> feature;
170 for (
const auto &axis : axes)
176 PointCloudIn rotated_cloud;
177 Eigen::Vector3f min, max;
178 rotateCloud (axis, theta, transformed_cloud, rotated_cloud, min, max);
181 for (
unsigned int i_proj = 0; i_proj < 3; i_proj++)
183 Eigen::MatrixXf distribution_matrix;
184 distribution_matrix.resize (number_of_bins_, number_of_bins_);
185 getDistributionMatrix (i_proj, min, max, rotated_cloud, distribution_matrix);
188 std::vector <float> moments;
189 computeCentralMoments (distribution_matrix, moments);
191 feature.insert (feature.end (), moments.begin (), moments.end ());
195 }
while (theta < 90.0f);
198 const float norm = std::accumulate(
199 feature.cbegin(), feature.cend(), 0.f, [](
const auto& sum,
const auto& val) {
200 return sum + std::abs(val);
203 if (norm < std::numeric_limits <float>::epsilon ())
206 invert_norm = 1.0f /
norm;
208 output.emplace_back ();
209 for (std::size_t i_dim = 0; i_dim < feature_size; i_dim++)
210 output.back().histogram[i_dim] = feature[i_dim] * invert_norm;
215 template <
typename Po
intInT,
typename Po
intOutT>
void
218 triangles_of_the_point_.clear ();
220 std::vector <unsigned int> dummy;
222 triangles_of_the_point_.resize (surface_->points. size (), dummy);
224 for (std::size_t i_triangle = 0; i_triangle < triangles_.size (); i_triangle++)
225 for (
const auto& vertex: triangles_[i_triangle].vertices)
226 triangles_of_the_point_[vertex].push_back (i_triangle);
230 template <
typename Po
intInT,
typename Po
intOutT>
void
233 std::vector <float> distances;
234 tree_->radiusSearch (point, support_radius_, local_points, distances);
236 for (
const auto& pt: local_points)
237 local_triangles.insert (triangles_of_the_point_[pt].begin (),
238 triangles_of_the_point_[pt].end ());
242 template <
typename Po
intInT,
typename Po
intOutT>
void
245 std::size_t number_of_triangles = local_triangles.size ();
247 std::vector<Eigen::Matrix3f, Eigen::aligned_allocator<Eigen::Matrix3f> > scatter_matrices;
248 std::vector <float> triangle_area (number_of_triangles), distance_weight (number_of_triangles);
250 scatter_matrices.reserve (number_of_triangles);
251 triangle_area.clear ();
252 distance_weight.clear ();
254 float total_area = 0.0f;
255 const float coeff = 1.0f / 12.0f;
256 const float coeff_1_div_3 = 1.0f / 3.0f;
258 Eigen::Vector3f feature_point (point.x, point.y, point.z);
260 for (
const auto& triangle: local_triangles)
262 Eigen::Vector3f pt[3];
263 for (
unsigned int i_vertex = 0; i_vertex < 3; i_vertex++)
265 const unsigned int index = triangles_[triangle].vertices[i_vertex];
266 pt[i_vertex] (0) = (*surface_)[index].x;
267 pt[i_vertex] (1) = (*surface_)[index].y;
268 pt[i_vertex] (2) = (*surface_)[index].z;
271 const float curr_area = ((pt[1] - pt[0]).cross (pt[2] - pt[0])).norm ();
272 triangle_area.push_back (curr_area);
273 total_area += curr_area;
275 distance_weight.push_back (std::pow (support_radius_ - (feature_point - (pt[0] + pt[1] + pt[2]) * coeff_1_div_3).norm (), 2.0f));
277 Eigen::Matrix3f curr_scatter_matrix;
278 curr_scatter_matrix.setZero ();
279 for (
const auto &i_pt : pt)
281 Eigen::Vector3f vec = i_pt - feature_point;
282 curr_scatter_matrix += vec * (vec.transpose ());
283 for (
const auto &j_pt : pt)
284 curr_scatter_matrix += vec * ((j_pt - feature_point).transpose ());
286 scatter_matrices.emplace_back (coeff * curr_scatter_matrix);
289 if (std::abs (total_area) < std::numeric_limits <float>::epsilon ())
290 total_area = 1.0f / total_area;
294 Eigen::Matrix3f overall_scatter_matrix;
295 overall_scatter_matrix.setZero ();
296 std::vector<float> total_weight (number_of_triangles);
297 const float denominator = 1.0f / 6.0f;
298 for (std::size_t i_triangle = 0; i_triangle < number_of_triangles; i_triangle++)
300 const float factor = distance_weight[i_triangle] * triangle_area[i_triangle] * total_area;
301 overall_scatter_matrix += factor * scatter_matrices[i_triangle];
302 total_weight[i_triangle] = factor * denominator;
305 Eigen::Vector3f v1, v2, v3;
306 computeEigenVectors (overall_scatter_matrix, v1, v2, v3);
310 std::size_t i_triangle = 0;
311 for (
const auto& triangle: local_triangles)
313 Eigen::Vector3f pt[3];
314 for (
unsigned int i_vertex = 0; i_vertex < 3; i_vertex++)
316 const unsigned int index = triangles_[triangle].vertices[i_vertex];
317 pt[i_vertex] (0) = (*surface_)[index].x;
318 pt[i_vertex] (1) = (*surface_)[index].y;
319 pt[i_vertex] (2) = (*surface_)[index].z;
322 float factor1 = 0.0f;
323 float factor3 = 0.0f;
324 for (
const auto &i_pt : pt)
326 Eigen::Vector3f vec = i_pt - feature_point;
327 factor1 += vec.dot (v1);
328 factor3 += vec.dot (v3);
330 h1 += total_weight[i_triangle] * factor1;
331 h3 += total_weight[i_triangle] * factor3;
335 if (h1 < 0.0f) v1 = -v1;
336 if (h3 < 0.0f) v3 = -v3;
340 lrf_matrix.row (0) = v1;
341 lrf_matrix.row (1) = v2;
342 lrf_matrix.row (2) = v3;
346 template <
typename Po
intInT,
typename Po
intOutT>
void
348 Eigen::Vector3f& major_axis, Eigen::Vector3f& middle_axis, Eigen::Vector3f& minor_axis)
const
350 Eigen::EigenSolver <Eigen::Matrix3f> eigen_solver;
353 Eigen::EigenSolver <Eigen::Matrix3f>::EigenvectorsType eigen_vectors;
354 Eigen::EigenSolver <Eigen::Matrix3f>::EigenvalueType eigen_values;
355 eigen_vectors = eigen_solver.eigenvectors ();
356 eigen_values = eigen_solver.eigenvalues ();
358 unsigned int temp = 0;
359 unsigned int major_index = 0;
360 unsigned int middle_index = 1;
361 unsigned int minor_index = 2;
363 if (eigen_values.real () (major_index) < eigen_values.real () (middle_index))
366 major_index = middle_index;
370 if (eigen_values.real () (major_index) < eigen_values.real () (minor_index))
373 major_index = minor_index;
377 if (eigen_values.real () (middle_index) < eigen_values.real () (minor_index))
380 minor_index = middle_index;
384 major_axis = eigen_vectors.col (major_index).real ();
385 middle_axis = eigen_vectors.col (middle_index).real ();
386 minor_axis = eigen_vectors.col (minor_index).real ();
390 template <
typename Po
intInT,
typename Po
intOutT>
void
393 const auto number_of_points = local_points.size ();
394 transformed_cloud.clear ();
395 transformed_cloud.reserve (number_of_points);
397 for (
const auto& idx: local_points)
399 Eigen::Vector3f transformed_point ((*surface_)[idx].x - point.x,
400 (*surface_)[idx].y - point.y,
401 (*surface_)[idx].z - point.z);
403 transformed_point = matrix * transformed_point;
406 new_point.x = transformed_point (0);
407 new_point.y = transformed_point (1);
408 new_point.z = transformed_point (2);
409 transformed_cloud.emplace_back (new_point);
414 template <
typename Po
intInT,
typename Po
intOutT>
void
417 Eigen::Matrix3f rotation_matrix;
418 const float x = axis.x;
419 const float y = axis.y;
420 const float z = axis.z;
421 const float rad =
M_PI / 180.0f;
422 const float cosine = std::cos (angle * rad);
423 const float sine = std::sin (angle * rad);
424 rotation_matrix << cosine + (1 - cosine) * x * x, (1 - cosine) * x * y - sine * z, (1 - cosine) * x * z + sine * y,
425 (1 - cosine) * y * x + sine * z, cosine + (1 - cosine) * y * y, (1 - cosine) * y * z - sine * x,
426 (1 - cosine) * z * x - sine * y, (1 - cosine) * z * y + sine * x, cosine + (1 - cosine) * z * z;
428 const auto number_of_points = cloud.size ();
430 rotated_cloud.header = cloud.header;
431 rotated_cloud.width = number_of_points;
432 rotated_cloud.height = 1;
433 rotated_cloud.clear ();
434 rotated_cloud.reserve (number_of_points);
436 min (0) = std::numeric_limits <float>::max ();
437 min (1) = std::numeric_limits <float>::max ();
438 min (2) = std::numeric_limits <float>::max ();
439 max (0) = -std::numeric_limits <float>::max ();
440 max (1) = -std::numeric_limits <float>::max ();
441 max (2) = -std::numeric_limits <float>::max ();
443 for (
const auto& pt: cloud.points)
445 Eigen::Vector3f point (pt.x, pt.y, pt.z);
446 point = rotation_matrix * point;
448 PointInT rotated_point;
449 rotated_point.x = point (0);
450 rotated_point.y = point (1);
451 rotated_point.z = point (2);
452 rotated_cloud.emplace_back (rotated_point);
454 for (
int i = 0; i < 3; ++i)
456 min(i) = std::min(min(i), point(i));
457 max(i) = std::max(max(i), point(i));
463 template <
typename Po
intInT,
typename Po
intOutT>
void
468 const unsigned int coord[3][2] = {
473 const float u_bin_length = (max (coord[projection][0]) - min (coord[projection][0])) / number_of_bins_;
474 const float v_bin_length = (max (coord[projection][1]) - min (coord[projection][1])) / number_of_bins_;
476 for (
const auto& pt: cloud.points)
478 Eigen::Vector3f point (pt.x, pt.y, pt.z);
480 const float u_length = point (coord[projection][0]) - min[coord[projection][0]];
481 const float v_length = point (coord[projection][1]) - min[coord[projection][1]];
483 const float u_ratio = u_length / u_bin_length;
484 unsigned int row =
static_cast <unsigned int> (u_ratio);
485 if (row == number_of_bins_) row--;
487 const float v_ratio = v_length / v_bin_length;
488 unsigned int col =
static_cast <unsigned int> (v_ratio);
489 if (col == number_of_bins_) col--;
491 matrix (row, col) += 1.0f;
494 matrix /= std::max<float> (1, cloud.size ());
498 template <
typename Po
intInT,
typename Po
intOutT>
void
504 for (
unsigned int i = 0; i < number_of_bins_; i++)
505 for (
unsigned int j = 0; j < number_of_bins_; j++)
507 const float m = matrix (i, j);
508 mean_i +=
static_cast <float> (i + 1) * m;
509 mean_j +=
static_cast <float> (j + 1) * m;
512 const unsigned int number_of_moments_to_compute = 4;
513 const float power[number_of_moments_to_compute][2] = {
519 float entropy = 0.0f;
520 moments.resize (number_of_moments_to_compute + 1, 0.0f);
521 for (
unsigned int i = 0; i < number_of_bins_; i++)
523 const float i_factor =
static_cast <float> (i + 1) - mean_i;
524 for (
unsigned int j = 0; j < number_of_bins_; j++)
526 const float j_factor =
static_cast <float> (j + 1) - mean_j;
527 const float m = matrix (i, j);
529 entropy -= m * std::log (m);
530 for (
unsigned int i_moment = 0; i_moment < number_of_moments_to_compute; i_moment++)
531 moments[i_moment] += std::pow (i_factor, power[i_moment][0]) * std::pow (j_factor, power[i_moment][1]) * m;
535 moments[number_of_moments_to_compute] = entropy;
void compute(PointCloudOut &output)
Base method for feature estimation for all points given in <setInputCloud (), setIndices ()> using th...
This class implements the method for extracting RoPS features presented in the article "Rotational Pr...
__device__ __host__ __forceinline__ float norm(const float3 &v1, const float3 &v2)
IndicesAllocator<> Indices
Type used for indices in PCL.