Point Cloud Library (PCL)  1.11.1
pyramid_feature_matching.hpp
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41 
42 #ifndef PCL_REGISTRATION_IMPL_PYRAMID_FEATURE_MATCHING_H_
43 #define PCL_REGISTRATION_IMPL_PYRAMID_FEATURE_MATCHING_H_
44 
45 #include <pcl/pcl_macros.h>
46 #include <pcl/console/print.h>
47 
48 
49 namespace pcl
50 {
51 
52 template <typename PointFeature> float
54  const PyramidFeatureHistogramPtr &pyramid_b)
55 {
56  // do a few consistency checks before and during the computation
57  if (pyramid_a->nr_dimensions != pyramid_b->nr_dimensions)
58  {
59  PCL_ERROR ("[pcl::PyramidFeatureMatching::comparePyramidFeatureHistograms] The two given pyramids have different numbers of dimensions: %u vs %u\n", pyramid_a->nr_dimensions, pyramid_b->nr_dimensions);
60  return -1;
61  }
62  if (pyramid_a->nr_levels != pyramid_b->nr_levels)
63  {
64  PCL_ERROR ("[pcl::PyramidFeatureMatching::comparePyramidFeatureHistograms] The two given pyramids have different numbers of levels: %u vs %u\n", pyramid_a->nr_levels, pyramid_b->nr_levels);
65  return -1;
66  }
67 
68 
69  // calculate for level 0 first
70  if (pyramid_a->hist_levels[0].hist.size () != pyramid_b->hist_levels[0].hist.size ())
71  {
72  PCL_ERROR ("[pcl::PyramidFeatureMatching::comparePyramidFeatureHistograms] The two given pyramids have different numbers of bins on level 0: %u vs %u\n", pyramid_a->hist_levels[0].hist.size (), pyramid_b->hist_levels[0].hist.size ());
73  return -1;
74  }
75  float match_count_level = 0.0f;
76  for (std::size_t bin_i = 0; bin_i < pyramid_a->hist_levels[0].hist.size (); ++bin_i)
77  {
78  if (pyramid_a->hist_levels[0].hist[bin_i] < pyramid_b->hist_levels[0].hist[bin_i])
79  match_count_level += static_cast<float> (pyramid_a->hist_levels[0].hist[bin_i]);
80  else
81  match_count_level += static_cast<float> (pyramid_b->hist_levels[0].hist[bin_i]);
82  }
83 
84 
85  float match_count = match_count_level;
86  for (std::size_t level_i = 1; level_i < pyramid_a->nr_levels; ++level_i)
87  {
88  if (pyramid_a->hist_levels[level_i].hist.size () != pyramid_b->hist_levels[level_i].hist.size ())
89  {
90  PCL_ERROR ("[pcl::PyramidFeatureMatching::comparePyramidFeatureHistograms] The two given pyramids have different numbers of bins on level %u: %u vs %u\n", level_i, pyramid_a->hist_levels[level_i].hist.size (), pyramid_b->hist_levels[level_i].hist.size ());
91  return -1;
92  }
93 
94  float match_count_prev_level = match_count_level;
95  match_count_level = 0.0f;
96  for (std::size_t bin_i = 0; bin_i < pyramid_a->hist_levels[level_i].hist.size (); ++bin_i)
97  {
98  if (pyramid_a->hist_levels[level_i].hist[bin_i] < pyramid_b->hist_levels[level_i].hist[bin_i])
99  match_count_level += static_cast<float> (pyramid_a->hist_levels[level_i].hist[bin_i]);
100  else
101  match_count_level += static_cast<float> (pyramid_b->hist_levels[level_i].hist[bin_i]);
102  }
103 
104  float level_normalization_factor = powf (2.0f, static_cast<float> (level_i));
105  match_count += (match_count_level - match_count_prev_level) / level_normalization_factor;
106  }
107 
108 
109  // include self-similarity factors
110  float self_similarity_a = static_cast<float> (pyramid_a->nr_features),
111  self_similarity_b = static_cast<float> (pyramid_b->nr_features);
112  PCL_DEBUG ("[pcl::PyramidFeatureMatching::comparePyramidFeatureHistograms] Self similarity measures: %f, %f\n", self_similarity_a, self_similarity_b);
113  match_count /= std::sqrt (self_similarity_a * self_similarity_b);
114 
115  return match_count;
116 }
117 
118 
119 template <typename PointFeature>
121  nr_dimensions (0), nr_levels (0), nr_features (0),
122  feature_representation_ (new DefaultPointRepresentation<PointFeature>),
123  is_computed_ (false),
124  hist_levels ()
125 {
126 }
127 
128 
129 template <typename PointFeature> void
131 {
132  std::size_t total_vector_size = 1;
133  for (std::vector<std::size_t>::iterator dim_it = bins_per_dimension.begin (); dim_it != bins_per_dimension.end (); ++dim_it)
134  total_vector_size *= *dim_it;
135 
136  hist.resize (total_vector_size, 0);
137 }
138 
139 
140 template <typename PointFeature> bool
141 PyramidFeatureHistogram<PointFeature>::initializeHistogram ()
142 {
143  // a few consistency checks before starting the computations
145  {
146  PCL_ERROR ("[pcl::PyramidFeatureHistogram::initializeHistogram] PCLBase initCompute failed\n");
147  return false;
148  }
149 
150  if (dimension_range_input_.empty ())
151  {
152  PCL_ERROR ("[pcl::PyramidFeatureHistogram::initializeHistogram] Input dimension range was not set\n");
153  return false;
154  }
155 
156  if (dimension_range_target_.empty ())
157  {
158  PCL_ERROR ("[pcl::PyramidFeatureHistogram::initializeHistogram] Target dimension range was not set\n");
159  return false;
160  }
161 
162  if (dimension_range_input_.size () != dimension_range_target_.size ())
163  {
164  PCL_ERROR ("[pcl::PyramidFeatureHistogram::initializeHistogram] Input and target dimension ranges do not agree in size: %u vs %u\n",
165  dimension_range_input_.size (), dimension_range_target_.size ());
166  return false;
167  }
168 
169 
170  nr_dimensions = dimension_range_target_.size ();
171  nr_features = input_->size ();
172  float D = 0.0f;
173  for (std::vector<std::pair<float, float> >::iterator range_it = dimension_range_target_.begin (); range_it != dimension_range_target_.end (); ++range_it)
174  {
175  float aux = range_it->first - range_it->second;
176  D += aux * aux;
177  }
178  D = std::sqrt (D);
179  nr_levels = static_cast<std::size_t> (std::ceil (std::log2(D)));
180  PCL_DEBUG ("[pcl::PyramidFeatureHistogram::initializeHistogram] Pyramid will have %u levels with a hyper-parallelepiped diagonal size of %f\n", nr_levels, D);
181 
182 
183  hist_levels.resize (nr_levels);
184  for (std::size_t level_i = 0; level_i < nr_levels; ++level_i)
185  {
186  std::vector<std::size_t> bins_per_dimension (nr_dimensions);
187  std::vector<float> bin_step (nr_dimensions);
188  for (std::size_t dim_i = 0; dim_i < nr_dimensions; ++dim_i)
189  {
190  bins_per_dimension[dim_i] =
191  static_cast<std::size_t> (std::ceil ((dimension_range_target_[dim_i].second - dimension_range_target_[dim_i].first) / (powf (2.0f, static_cast<float> (level_i)) * std::sqrt (static_cast<float> (nr_dimensions)))));
192  bin_step[dim_i] = powf (2.0f, static_cast<float> (level_i)) * std::sqrt (static_cast<float> (nr_dimensions));
193  }
194  hist_levels[level_i] = PyramidFeatureHistogramLevel (bins_per_dimension, bin_step);
195 
196  PCL_DEBUG ("[pcl::PyramidFeatureHistogram::initializeHistogram] Created vector of size %u at level %u\nwith #bins per dimension:", hist_levels.back ().hist.size (), level_i);
197  for (std::size_t dim_i = 0; dim_i < nr_dimensions; ++dim_i)
198  PCL_DEBUG ("%u ", bins_per_dimension[dim_i]);
199  PCL_DEBUG ("\n");
200  }
201 
202  return true;
203 }
204 
205 
206 template <typename PointFeature> unsigned int&
207 PyramidFeatureHistogram<PointFeature>::at (std::vector<std::size_t> &access,
208  std::size_t &level)
209 {
210  if (access.size () != nr_dimensions)
211  {
212  PCL_ERROR ("[pcl::PyramidFeatureHistogram::at] Cannot access histogram position because the access point does not have the right number of dimensions\n");
213  return hist_levels.front ().hist.front ();
214  }
215  if (level >= hist_levels.size ())
216  {
217  PCL_ERROR ("[pcl::PyramidFeatureHistogram::at] Trying to access a too large level\n");
218  return hist_levels.front ().hist.front ();
219  }
220 
221  std::size_t vector_position = 0;
222  std::size_t dim_accumulator = 1;
223 
224  for (int i = static_cast<int> (access.size ()) - 1; i >= 0; --i)
225  {
226  vector_position += access[i] * dim_accumulator;
227  dim_accumulator *= hist_levels[level].bins_per_dimension[i];
228  }
229 
230  return hist_levels[level].hist[vector_position];
231 }
232 
233 
234 template <typename PointFeature> unsigned int&
235 PyramidFeatureHistogram<PointFeature>::at (std::vector<float> &feature,
236  std::size_t &level)
237 {
238  if (feature.size () != nr_dimensions)
239  {
240  PCL_ERROR ("[pcl::PyramidFeatureHistogram::at] The given feature vector does not match the feature dimensions of the pyramid histogram: %u vs %u\n", feature.size (), nr_dimensions);
241  return hist_levels.front ().hist.front ();
242  }
243  if (level >= hist_levels.size ())
244  {
245  PCL_ERROR ("[pcl::PyramidFeatureHistogram::at] Trying to access a too large level\n");
246  return hist_levels.front ().hist.front ();
247  }
248 
249  std::vector<std::size_t> access;
250  for (std::size_t dim_i = 0; dim_i < nr_dimensions; ++dim_i)
251  access.push_back (static_cast<std::size_t> (std::floor ((feature[dim_i] - dimension_range_target_[dim_i].first) / hist_levels[level].bin_step[dim_i])));
252 
253  return at (access, level);
254 }
255 
256 
257 template <typename PointFeature> void
258 PyramidFeatureHistogram<PointFeature>::convertFeatureToVector (const PointFeature &feature,
259  std::vector<float> &feature_vector)
260 {
261  // convert feature to vector representation
262  feature_vector.resize (feature_representation_->getNumberOfDimensions ());
263  feature_representation_->vectorize (feature, feature_vector);
264 
265  // adapt the values from the input range to the target range
266  for (std::size_t i = 0; i < feature_vector.size (); ++i)
267  feature_vector[i] = (feature_vector[i] - dimension_range_input_[i].first) / (dimension_range_input_[i].second - dimension_range_input_[i].first) *
268  (dimension_range_target_[i].second - dimension_range_target_[i].first) + dimension_range_target_[i].first;
269 }
270 
271 
272 template <typename PointFeature> void
274 {
275  if (!initializeHistogram ())
276  return;
277 
278  for (const auto& point: *input_)
279  {
280  std::vector<float> feature_vector;
281  convertFeatureToVector (point, feature_vector);
282  addFeature (feature_vector);
283  }
284 
285  is_computed_ = true;
286 }
287 
288 
289 template <typename PointFeature> void
290 PyramidFeatureHistogram<PointFeature>::addFeature (std::vector<float> &feature)
291 {
292  for (std::size_t level_i = 0; level_i < nr_levels; ++level_i)
293  at (feature, level_i) ++;
294 }
295 
296 } // namespace pcl
297 
298 #define PCL_INSTANTIATE_PyramidFeatureHistogram(PointFeature) template class PCL_EXPORTS pcl::PyramidFeatureHistogram<PointFeature>;
299 
300 #endif /* PCL_REGISTRATION_IMPL_PYRAMID_FEATURE_MATCHING_H_ */
301 
DefaultPointRepresentation extends PointRepresentation to define default behavior for common point ty...
bool initCompute()
This method should get called before starting the actual computation.
Definition: pcl_base.hpp:138
Class that compares two sets of features by using a multiscale representation of the features inside ...
void compute()
The central method for inserting the feature set inside the pyramid and obtaining the complete pyrami...
static float comparePyramidFeatureHistograms(const PyramidFeatureHistogramPtr &pyramid_a, const PyramidFeatureHistogramPtr &pyramid_b)
Static method for comparing two pyramid histograms that returns a floating point value between 0 and ...
PyramidFeatureHistogram()
Empty constructor that instantiates the feature representation variable.
Defines all the PCL and non-PCL macros used.