Point Cloud Library (PCL)  1.9.1-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 
75  typedef boost::shared_ptr<SampleConsensusModelLine> Ptr;
76 
77  /** \brief Constructor for base SampleConsensusModelLine.
78  * \param[in] cloud the input point cloud dataset
79  * \param[in] random if true set the random seed to the current time, else set to 12345 (default: false)
80  */
81  SampleConsensusModelLine (const PointCloudConstPtr &cloud, bool random = false)
82  : SampleConsensusModel<PointT> (cloud, random)
83  {
84  model_name_ = "SampleConsensusModelLine";
85  sample_size_ = 2;
86  model_size_ = 6;
87  }
88 
89  /** \brief Constructor for base SampleConsensusModelLine.
90  * \param[in] cloud the input point cloud dataset
91  * \param[in] indices a vector of point indices to be used from \a cloud
92  * \param[in] random if true set the random seed to the current time, else set to 12345 (default: false)
93  */
94  SampleConsensusModelLine (const PointCloudConstPtr &cloud,
95  const std::vector<int> &indices,
96  bool random = false)
97  : SampleConsensusModel<PointT> (cloud, indices, random)
98  {
99  model_name_ = "SampleConsensusModelLine";
100  sample_size_ = 2;
101  model_size_ = 6;
102  }
103 
104  /** \brief Empty destructor */
106 
107  /** \brief Check whether the given index samples can form a valid line model, compute the model coefficients from
108  * these samples and store them internally in model_coefficients_. The line coefficients are represented by a
109  * point and a line direction
110  * \param[in] samples the point indices found as possible good candidates for creating a valid model
111  * \param[out] model_coefficients the resultant model coefficients
112  */
113  bool
114  computeModelCoefficients (const std::vector<int> &samples,
115  Eigen::VectorXf &model_coefficients) const override;
116 
117  /** \brief Compute all squared distances from the cloud data to a given line model.
118  * \param[in] model_coefficients the coefficients of a line model that we need to compute distances to
119  * \param[out] distances the resultant estimated squared distances
120  */
121  void
122  getDistancesToModel (const Eigen::VectorXf &model_coefficients,
123  std::vector<double> &distances) const override;
124 
125  /** \brief Select all the points which respect the given model coefficients as inliers.
126  * \param[in] model_coefficients the coefficients of a line model that we need to compute distances to
127  * \param[in] threshold a maximum admissible distance threshold for determining the inliers from the outliers
128  * \param[out] inliers the resultant model inliers
129  */
130  void
131  selectWithinDistance (const Eigen::VectorXf &model_coefficients,
132  const double threshold,
133  std::vector<int> &inliers) override;
134 
135  /** \brief Count all the points which respect the given model coefficients as inliers.
136  *
137  * \param[in] model_coefficients the coefficients of a model that we need to compute distances to
138  * \param[in] threshold maximum admissible distance threshold for determining the inliers from the outliers
139  * \return the resultant number of inliers
140  */
141  int
142  countWithinDistance (const Eigen::VectorXf &model_coefficients,
143  const double threshold) const override;
144 
145  /** \brief Recompute the line coefficients using the given inlier set and return them to the user.
146  * @note: these are the coefficients of the line model after refinement (e.g. after SVD)
147  * \param[in] inliers the data inliers found as supporting the model
148  * \param[in] model_coefficients the initial guess for the model coefficients
149  * \param[out] optimized_coefficients the resultant recomputed coefficients after optimization
150  */
151  void
152  optimizeModelCoefficients (const std::vector<int> &inliers,
153  const Eigen::VectorXf &model_coefficients,
154  Eigen::VectorXf &optimized_coefficients) const override;
155 
156  /** \brief Create a new point cloud with inliers projected onto the line model.
157  * \param[in] inliers the data inliers that we want to project on the line model
158  * \param[in] model_coefficients the *normalized* coefficients of a line model
159  * \param[out] projected_points the resultant projected points
160  * \param[in] copy_data_fields set to true if we need to copy the other data fields
161  */
162  void
163  projectPoints (const std::vector<int> &inliers,
164  const Eigen::VectorXf &model_coefficients,
165  PointCloud &projected_points,
166  bool copy_data_fields = true) const override;
167 
168  /** \brief Verify whether a subset of indices verifies the given line model coefficients.
169  * \param[in] indices the data indices that need to be tested against the line model
170  * \param[in] model_coefficients the line model coefficients
171  * \param[in] threshold a maximum admissible distance threshold for determining the inliers from the outliers
172  */
173  bool
174  doSamplesVerifyModel (const std::set<int> &indices,
175  const Eigen::VectorXf &model_coefficients,
176  const double threshold) const override;
177 
178  /** \brief Return an unique id for this model (SACMODEL_LINE). */
179  inline pcl::SacModel
180  getModelType () const override { return (SACMODEL_LINE); }
181 
182  protected:
185 
186  /** \brief Check if a sample of indices results in a good sample of points
187  * indices.
188  * \param[in] samples the resultant index samples
189  */
190  bool
191  isSampleGood (const std::vector<int> &samples) const override;
192  };
193 }
194 
195 #ifdef PCL_NO_PRECOMPILE
196 #include <pcl/sample_consensus/impl/sac_model_line.hpp>
197 #endif
SampleConsensusModel< PointT >::PointCloud PointCloud
SampleConsensusModelLine defines a model for 3D line segmentation.
SampleConsensusModel< PointT >::PointCloudPtr PointCloudPtr
SampleConsensusModelLine(const PointCloudConstPtr &cloud, const std::vector< int > &indices, bool random=false)
Constructor for base SampleConsensusModelLine.
This file defines compatibility wrappers for low level I/O functions.
Definition: convolution.h:44
unsigned int model_size_
The number of coefficients in the model.
Definition: sac_model.h:560
SampleConsensusModel< PointT >::PointCloudConstPtr PointCloudConstPtr
PointCloud::ConstPtr PointCloudConstPtr
Definition: sac_model.h:69
SampleConsensusModelLine(const PointCloudConstPtr &cloud, bool random=false)
Constructor for base SampleConsensusModelLine.
bool computeModelCoefficients(const std::vector< int > &samples, Eigen::VectorXf &model_coefficients) const override
Check whether the given index samples can form a valid line model, compute the model coefficients fro...
SampleConsensusModel represents the base model class.
Definition: sac_model.h:65
void selectWithinDistance(const Eigen::VectorXf &model_coefficients, const double threshold, std::vector< int > &inliers) override
Select all the points which respect the given model coefficients as inliers.
~SampleConsensusModelLine()
Empty destructor.
std::string model_name_
The model name.
Definition: sac_model.h:519
boost::shared_ptr< SampleConsensusModelLine > Ptr
PointCloud::Ptr PointCloudPtr
Definition: sac_model.h:70
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 an unique id for this model (SACMODEL_LINE).
void optimizeModelCoefficients(const std::vector< int > &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.
A point structure representing Euclidean xyz coordinates, and the RGB color.
int countWithinDistance(const Eigen::VectorXf &model_coefficients, const double threshold) const override
Count all the points which respect the given model coefficients as inliers.
bool isSampleGood(const std::vector< int > &samples) const override
Check if a sample of indices results in a good sample of points indices.
void projectPoints(const std::vector< int > &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.
unsigned int sample_size_
The size of a sample from which the model is computed.
Definition: sac_model.h:557
bool doSamplesVerifyModel(const std::set< int > &indices, const Eigen::VectorXf &model_coefficients, const double threshold) const override
Verify whether a subset of indices verifies the given line model coefficients.