Point Cloud Library (PCL) 1.14.0
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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
46namespace pcl
47{
48 /** \brief SampleConsensusModelLine defines a model for 3D line segmentation.
49 * The model coefficients are defined as:
50 * - \b point_on_line.x : the X coordinate of a point on the line
51 * - \b point_on_line.y : the Y coordinate of a point on the line
52 * - \b point_on_line.z : the Z coordinate of a point on the line
53 * - \b line_direction.x : the X coordinate of a line's direction
54 * - \b line_direction.y : the Y coordinate of a line's direction
55 * - \b line_direction.z : the Z coordinate of a line's direction
56 *
57 * \author Radu B. Rusu
58 * \ingroup sample_consensus
59 */
60 template <typename PointT>
62 {
63 public:
69
73
74 using Ptr = shared_ptr<SampleConsensusModelLine<PointT> >;
75 using ConstPtr = shared_ptr<const SampleConsensusModelLine<PointT>>;
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 */
95 const Indices &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 */
105 ~SampleConsensusModelLine () override = default;
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 Indices &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 Indices &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 std::size_t
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 Indices &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 Indices &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<index_t> &indices,
175 const Eigen::VectorXf &model_coefficients,
176 const double threshold) const override;
177
178 /** \brief Return a 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 Indices &samples) const override;
192 };
193}
194
195#ifdef PCL_NO_PRECOMPILE
196#include <pcl/sample_consensus/impl/sac_model_line.hpp>
197#endif
PointCloud represents the base class in PCL for storing collections of 3D points.
SampleConsensusModel represents the base model class.
Definition sac_model.h:71
unsigned int sample_size_
The size of a sample from which the model is computed.
Definition sac_model.h:589
typename PointCloud::ConstPtr PointCloudConstPtr
Definition sac_model.h:74
IndicesPtr indices_
A pointer to the vector of point indices to use.
Definition sac_model.h:557
PointCloudConstPtr input_
A boost shared pointer to the point cloud data array.
Definition sac_model.h:554
virtual bool isModelValid(const Eigen::VectorXf &model_coefficients) const
Check whether a model is valid given the user constraints.
Definition sac_model.h:528
std::string model_name_
The model name.
Definition sac_model.h:551
unsigned int model_size_
The number of coefficients in the model.
Definition sac_model.h:592
typename PointCloud::Ptr PointCloudPtr
Definition sac_model.h:75
std::vector< double > error_sqr_dists_
A vector holding the distances to the computed model.
Definition sac_model.h:586
SampleConsensusModelLine defines a model for 3D line segmentation.
typename SampleConsensusModel< PointT >::PointCloudPtr PointCloudPtr
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...
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.
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.
bool isSampleGood(const Indices &samples) const override
Check if a sample of indices results in a good sample of points indices.
pcl::SacModel getModelType() const override
Return a unique id for this model (SACMODEL_LINE).
SampleConsensusModelLine(const PointCloudConstPtr &cloud, bool random=false)
Constructor for base SampleConsensusModelLine.
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.
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.
~SampleConsensusModelLine() override=default
Empty destructor.
typename SampleConsensusModel< PointT >::PointCloudConstPtr PointCloudConstPtr
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.
shared_ptr< const SampleConsensusModelLine< PointT > > ConstPtr
typename SampleConsensusModel< PointT >::PointCloud PointCloud
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.
shared_ptr< SampleConsensusModelLine< PointT > > Ptr
@ SACMODEL_LINE
Definition model_types.h:48
IndicesAllocator<> Indices
Type used for indices in PCL.
Definition types.h:133
A point structure representing Euclidean xyz coordinates, and the RGB color.