Point Cloud Library (PCL)  1.10.1-dev
sac_model_line.h
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40 
41 #pragma once
42 
43 #include <pcl/sample_consensus/sac_model.h>
44 #include <pcl/sample_consensus/model_types.h>
45 #include <pcl/common/eigen.h>
46 
47 namespace pcl
48 {
49  /** \brief SampleConsensusModelLine defines a model for 3D line segmentation.
50  * The model coefficients are defined as:
51  * - \b point_on_line.x : the X coordinate of a point on the line
52  * - \b point_on_line.y : the Y coordinate of a point on the line
53  * - \b point_on_line.z : the Z coordinate of a point on the line
54  * - \b line_direction.x : the X coordinate of a line's direction
55  * - \b line_direction.y : the Y coordinate of a line's direction
56  * - \b line_direction.z : the Z coordinate of a line's direction
57  *
58  * \author Radu B. Rusu
59  * \ingroup sample_consensus
60  */
61  template <typename PointT>
63  {
64  public:
70 
74 
77 
78  /** \brief Constructor for base SampleConsensusModelLine.
79  * \param[in] cloud the input point cloud dataset
80  * \param[in] random if true set the random seed to the current time, else set to 12345 (default: false)
81  */
82  SampleConsensusModelLine (const PointCloudConstPtr &cloud, bool random = false)
83  : SampleConsensusModel<PointT> (cloud, random)
84  {
85  model_name_ = "SampleConsensusModelLine";
86  sample_size_ = 2;
87  model_size_ = 6;
88  }
89 
90  /** \brief Constructor for base SampleConsensusModelLine.
91  * \param[in] cloud the input point cloud dataset
92  * \param[in] indices a vector of point indices to be used from \a cloud
93  * \param[in] random if true set the random seed to the current time, else set to 12345 (default: false)
94  */
96  const Indices &indices,
97  bool random = false)
98  : SampleConsensusModel<PointT> (cloud, indices, random)
99  {
100  model_name_ = "SampleConsensusModelLine";
101  sample_size_ = 2;
102  model_size_ = 6;
103  }
104 
105  /** \brief Empty destructor */
107 
108  /** \brief Check whether the given index samples can form a valid line model, compute the model coefficients from
109  * these samples and store them internally in model_coefficients_. The line coefficients are represented by a
110  * point and a line direction
111  * \param[in] samples the point indices found as possible good candidates for creating a valid model
112  * \param[out] model_coefficients the resultant model coefficients
113  */
114  bool
115  computeModelCoefficients (const Indices &samples,
116  Eigen::VectorXf &model_coefficients) const override;
117 
118  /** \brief Compute all squared distances from the cloud data to a given line model.
119  * \param[in] model_coefficients the coefficients of a line model that we need to compute distances to
120  * \param[out] distances the resultant estimated squared distances
121  */
122  void
123  getDistancesToModel (const Eigen::VectorXf &model_coefficients,
124  std::vector<double> &distances) const override;
125 
126  /** \brief Select all the points which respect the given model coefficients as inliers.
127  * \param[in] model_coefficients the coefficients of a line model that we need to compute distances to
128  * \param[in] threshold a maximum admissible distance threshold for determining the inliers from the outliers
129  * \param[out] inliers the resultant model inliers
130  */
131  void
132  selectWithinDistance (const Eigen::VectorXf &model_coefficients,
133  const double threshold,
134  Indices &inliers) override;
135 
136  /** \brief Count all the points which respect the given model coefficients as inliers.
137  *
138  * \param[in] model_coefficients the coefficients of a model that we need to compute distances to
139  * \param[in] threshold maximum admissible distance threshold for determining the inliers from the outliers
140  * \return the resultant number of inliers
141  */
142  std::size_t
143  countWithinDistance (const Eigen::VectorXf &model_coefficients,
144  const double threshold) const override;
145 
146  /** \brief Recompute the line coefficients using the given inlier set and return them to the user.
147  * @note: these are the coefficients of the line model after refinement (e.g. after SVD)
148  * \param[in] inliers the data inliers found as supporting the model
149  * \param[in] model_coefficients the initial guess for the model coefficients
150  * \param[out] optimized_coefficients the resultant recomputed coefficients after optimization
151  */
152  void
153  optimizeModelCoefficients (const Indices &inliers,
154  const Eigen::VectorXf &model_coefficients,
155  Eigen::VectorXf &optimized_coefficients) const override;
156 
157  /** \brief Create a new point cloud with inliers projected onto the line model.
158  * \param[in] inliers the data inliers that we want to project on the line model
159  * \param[in] model_coefficients the *normalized* coefficients of a line model
160  * \param[out] projected_points the resultant projected points
161  * \param[in] copy_data_fields set to true if we need to copy the other data fields
162  */
163  void
164  projectPoints (const Indices &inliers,
165  const Eigen::VectorXf &model_coefficients,
166  PointCloud &projected_points,
167  bool copy_data_fields = true) const override;
168 
169  /** \brief Verify whether a subset of indices verifies the given line model coefficients.
170  * \param[in] indices the data indices that need to be tested against the line model
171  * \param[in] model_coefficients the line model coefficients
172  * \param[in] threshold a maximum admissible distance threshold for determining the inliers from the outliers
173  */
174  bool
175  doSamplesVerifyModel (const std::set<index_t> &indices,
176  const Eigen::VectorXf &model_coefficients,
177  const double threshold) const override;
178 
179  /** \brief Return a unique id for this model (SACMODEL_LINE). */
180  inline pcl::SacModel
181  getModelType () const override { return (SACMODEL_LINE); }
182 
183  protected:
186 
187  /** \brief Check if a sample of indices results in a good sample of points
188  * indices.
189  * \param[in] samples the resultant index samples
190  */
191  bool
192  isSampleGood (const Indices &samples) const override;
193  };
194 }
195 
196 #ifdef PCL_NO_PRECOMPILE
197 #include <pcl/sample_consensus/impl/sac_model_line.hpp>
198 #endif
SampleConsensusModelLine defines a model for 3D line segmentation.
std::vector< index_t > Indices
Type used for indices in PCL.
Definition: types.h:142
unsigned int model_size_
The number of coefficients in the model.
Definition: sac_model.h:566
bool isSampleGood(const Indices &samples) const override
Check if a sample of indices results in a good sample of points indices.
SampleConsensusModelLine(const PointCloudConstPtr &cloud, bool random=false)
Constructor for base SampleConsensusModelLine.
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 line model.
typename PointCloud::Ptr PointCloudPtr
Definition: sac_model.h:75
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 line model coefficients.
SampleConsensusModel represents the base model class.
Definition: sac_model.h:70
~SampleConsensusModelLine()
Empty destructor.
std::string model_name_
The model name.
Definition: sac_model.h:525
typename PointCloud::ConstPtr PointCloudConstPtr
Definition: sac_model.h:74
PointCloud represents the base class in PCL for storing collections of 3D points. ...
SacModel
Definition: model_types.h:45
pcl::SacModel getModelType() const override
Return a unique id for this model (SACMODEL_LINE).
shared_ptr< const SampleConsensusModel< PointT > > ConstPtr
Definition: sac_model.h:79
void optimizeModelCoefficients(const Indices &inliers, const Eigen::VectorXf &model_coefficients, Eigen::VectorXf &optimized_coefficients) const override
Recompute the line coefficients using the given inlier set and return them to the user...
void getDistancesToModel(const Eigen::VectorXf &model_coefficients, std::vector< double > &distances) const override
Compute all squared distances from the cloud data to a given line model.
SampleConsensusModelLine(const PointCloudConstPtr &cloud, const Indices &indices, bool random=false)
Constructor for base SampleConsensusModelLine.
A point structure representing Euclidean xyz coordinates, and the RGB color.
shared_ptr< SampleConsensusModel< PointT > > Ptr
Definition: sac_model.h:78
boost::shared_ptr< T > shared_ptr
Alias for boost::shared_ptr.
Definition: memory.h:81
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.
bool computeModelCoefficients(const Indices &samples, Eigen::VectorXf &model_coefficients) const override
Check whether the given index samples can form a valid line model, compute the model coefficients fro...
unsigned int sample_size_
The size of a sample from which the model is computed.
Definition: sac_model.h:563