Point Cloud Library (PCL)  1.7.2
correspondence_rejection_sample_consensus.hpp
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40 #ifndef PCL_REGISTRATION_IMPL_CORRESPONDENCE_REJECTION_SAMPLE_CONSENSUS_HPP_
41 #define PCL_REGISTRATION_IMPL_CORRESPONDENCE_REJECTION_SAMPLE_CONSENSUS_HPP_
42 
43 #include <boost/unordered_map.hpp>
44 
45 ///////////////////////////////////////////////////////////////////////////////////////////
46 template <typename PointT> void
48  const typename pcl::registration::CorrespondenceRejectorSampleConsensus<PointT>::PointCloudConstPtr &cloud)
49 {
50  setInputSource (cloud);
51 }
52 
53 ///////////////////////////////////////////////////////////////////////////////////////////
54 template <typename PointT> typename pcl::registration::CorrespondenceRejectorSampleConsensus<PointT>::PointCloudConstPtr const
56 {
57  return (getInputSource ());
58 }
59 
60 ///////////////////////////////////////////////////////////////////////////////////////////
61 template <typename PointT> void
63  const typename pcl::registration::CorrespondenceRejectorSampleConsensus<PointT>::PointCloudConstPtr &cloud)
64 {
65  setInputTarget (cloud);
66 }
67 
68 ///////////////////////////////////////////////////////////////////////////////////////////
69 template <typename PointT> void
71  int max_iterations)
72 {
73  setMaximumIterations (max_iterations);
74 }
75 
76 ///////////////////////////////////////////////////////////////////////////////////////////
77 template <typename PointT> int
79 {
80  return (getMaximumIterations ());
81 }
82 
83 ///////////////////////////////////////////////////////////////////////////////////////////
84 template <typename PointT> void
86  const pcl::Correspondences& original_correspondences,
87  pcl::Correspondences& remaining_correspondences)
88 {
89  if (!input_)
90  {
91  PCL_ERROR ("[pcl::registration::%s::getRemainingCorrespondences] No input cloud dataset was given!\n", getClassName ().c_str ());
92  return;
93  }
94 
95  if (!target_)
96  {
97  PCL_ERROR ("[pcl::registration::%s::getRemainingCorrespondences] No input target dataset was given!\n", getClassName ().c_str ());
98  return;
99  }
100 
101  if (save_inliers_)
102  inlier_indices_.clear ();
103 
104  int nr_correspondences = static_cast<int> (original_correspondences.size ());
105  std::vector<int> source_indices (nr_correspondences);
106  std::vector<int> target_indices (nr_correspondences);
107 
108  // Copy the query-match indices
109  for (size_t i = 0; i < original_correspondences.size (); ++i)
110  {
111  source_indices[i] = original_correspondences[i].index_query;
112  target_indices[i] = original_correspondences[i].index_match;
113  }
114 
115  // from pcl/registration/icp.hpp:
116  std::vector<int> source_indices_good;
117  std::vector<int> target_indices_good;
118  {
119  // From the set of correspondences found, attempt to remove outliers
120  // Create the registration model
121  typedef typename pcl::SampleConsensusModelRegistration<PointT>::Ptr SampleConsensusModelRegistrationPtr;
122  SampleConsensusModelRegistrationPtr model;
123  model.reset (new pcl::SampleConsensusModelRegistration<PointT> (input_, source_indices));
124  // Pass the target_indices
125  model->setInputTarget (target_, target_indices);
126  // Create a RANSAC model
127  pcl::RandomSampleConsensus<PointT> sac (model, inlier_threshold_);
128  sac.setMaxIterations (max_iterations_);
129 
130  // Compute the set of inliers
131  if (!sac.computeModel ())
132  {
133  remaining_correspondences = original_correspondences;
134  best_transformation_.setIdentity ();
135  return;
136  }
137  else
138  {
139  if (refine_ && !sac.refineModel ())
140  {
141  PCL_ERROR ("[pcl::registration::CorrespondenceRejectorSampleConsensus::getRemainingCorrespondences] Could not refine the model! Returning an empty solution.\n");
142  return;
143  }
144 
145  std::vector<int> inliers;
146  sac.getInliers (inliers);
147 
148  if (inliers.size () < 3)
149  {
150  remaining_correspondences = original_correspondences;
151  best_transformation_.setIdentity ();
152  return;
153  }
154  boost::unordered_map<int, int> index_to_correspondence;
155  for (int i = 0; i < nr_correspondences; ++i)
156  index_to_correspondence[original_correspondences[i].index_query] = i;
157 
158  remaining_correspondences.resize (inliers.size ());
159  for (size_t i = 0; i < inliers.size (); ++i)
160  remaining_correspondences[i] = original_correspondences[index_to_correspondence[inliers[i]]];
161 
162  if (save_inliers_)
163  {
164  inlier_indices_.reserve (inliers.size ());
165  for (size_t i = 0; i < inliers.size (); ++i)
166  inlier_indices_.push_back (index_to_correspondence[inliers[i]]);
167  }
168 
169  // get best transformation
170  Eigen::VectorXf model_coefficients;
171  sac.getModelCoefficients (model_coefficients);
172  best_transformation_.row (0) = model_coefficients.segment<4>(0);
173  best_transformation_.row (1) = model_coefficients.segment<4>(4);
174  best_transformation_.row (2) = model_coefficients.segment<4>(8);
175  best_transformation_.row (3) = model_coefficients.segment<4>(12);
176  }
177  }
178 }
179 
180 #endif // PCL_REGISTRATION_IMPL_CORRESPONDENCE_REJECTION_SAMPLE_CONSENSUS_HPP_
boost::shared_ptr< SampleConsensusModelRegistration > Ptr
SampleConsensusModelRegistration defines a model for Point-To-Point registration outlier rejection...
virtual void setTargetCloud(const PointCloudConstPtr &cloud)
Provide a target point cloud dataset (must contain XYZ data!)
bool computeModel(int debug_verbosity_level=0)
Compute the actual model and find the inliers.
Definition: ransac.hpp:48
PointCloudConstPtr const getInputCloud()
Get a pointer to the input point cloud dataset target.
void setMaxIterations(int max_iterations)
Set the maximum number of iterations.
void getInliers(std::vector< int > &inliers)
Return the best set of inliers found so far for this model.
Definition: sac.h:300
std::vector< pcl::Correspondence, Eigen::aligned_allocator< pcl::Correspondence > > Correspondences
void getModelCoefficients(Eigen::VectorXf &model_coefficients)
Return the model coefficients of the best model found so far.
Definition: sac.h:306
virtual void setInputCloud(const PointCloudConstPtr &cloud)
Provide a source point cloud dataset (must contain XYZ data!)
void setMaxIterations(int max_iterations)
Set the maximum number of iterations.
Definition: sac.h:150
virtual bool refineModel(const double sigma=3.0, const unsigned int max_iterations=1000)
Refine the model found.
Definition: sac.h:179
RandomSampleConsensus represents an implementation of the RANSAC (RAndom SAmple Consensus) algorithm...
Definition: ransac.h:56
void getRemainingCorrespondences(const pcl::Correspondences &original_correspondences, pcl::Correspondences &remaining_correspondences)
Get a list of valid correspondences after rejection from the original set of correspondences.