Point Cloud Library (PCL) 1.13.0
sac_model_normal_sphere.h
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37 * $Id: sac_model_normal_sphere.h schrandt $
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40
41#pragma once
42
43#include <pcl/sample_consensus/sac_model.h>
44#include <pcl/sample_consensus/sac_model_sphere.h>
45#include <pcl/sample_consensus/model_types.h>
46#include <pcl/memory.h>
47#include <pcl/pcl_macros.h>
48
49namespace pcl
50{
51 /** \brief @b SampleConsensusModelNormalSphere defines a model for 3D sphere
52 * segmentation using additional surface normal constraints. Basically this
53 * means that checking for inliers will not only involve a "distance to
54 * model" criterion, but also an additional "maximum angular deviation"
55 * between the sphere's normal and the inlier points normals.
56 *
57 * The model coefficients are defined as:
58 * <ul>
59 * <li><b>center.x</b> : the X coordinate of the sphere's center
60 * <li><b>center.y</b> : the Y coordinate of the sphere's center
61 * <li><b>center.z</b> : the Z coordinate of the sphere's center
62 * <li><b>radius</b> : radius of the sphere
63 * </ul>
64 *
65 * \author Stefan Schrandt
66 * \ingroup sample_consensus
67 */
68 template <typename PointT, typename PointNT>
70 {
71 public:
80
84
87
88 using Ptr = shared_ptr<SampleConsensusModelNormalSphere<PointT, PointNT> >;
89 using ConstPtr = shared_ptr<const SampleConsensusModelNormalSphere<PointT, PointNT>>;
90
91 /** \brief Constructor for base SampleConsensusModelNormalSphere.
92 * \param[in] cloud the input point cloud dataset
93 * \param[in] random if true set the random seed to the current time, else set to 12345 (default: false)
94 */
96 bool random = false)
97 : SampleConsensusModelSphere<PointT> (cloud, random)
99 {
100 model_name_ = "SampleConsensusModelNormalSphere";
101 sample_size_ = 4;
102 model_size_ = 4;
103 }
104
105 /** \brief Constructor for base SampleConsensusModelNormalSphere.
106 * \param[in] cloud the input point cloud dataset
107 * \param[in] indices a vector of point indices to be used from \a cloud
108 * \param[in] random if true set the random seed to the current time, else set to 12345 (default: false)
109 */
111 const Indices &indices,
112 bool random = false)
113 : SampleConsensusModelSphere<PointT> (cloud, indices, random)
115 {
116 model_name_ = "SampleConsensusModelNormalSphere";
117 sample_size_ = 4;
118 model_size_ = 4;
119 }
120
121 /** \brief Empty destructor */
123
124 /** \brief Select all the points which respect the given model coefficients as inliers.
125 * \param[in] model_coefficients the coefficients of a sphere model that we need to compute distances to
126 * \param[in] threshold a maximum admissible distance threshold for determining the inliers from the outliers
127 * \param[out] inliers the resultant model inliers
128 */
129 void
130 selectWithinDistance (const Eigen::VectorXf &model_coefficients,
131 const double threshold,
132 Indices &inliers) override;
133
134 /** \brief Count all the points which respect the given model coefficients as inliers.
135 * \param[in] model_coefficients the coefficients of a model that we need to compute distances to
136 * \param[in] threshold maximum admissible distance threshold for determining the inliers from the outliers
137 * \return the resultant number of inliers
138 */
139 std::size_t
140 countWithinDistance (const Eigen::VectorXf &model_coefficients,
141 const double threshold) const override;
142
143 /** \brief Compute all distances from the cloud data to a given sphere model.
144 * \param[in] model_coefficients the coefficients of a sphere model that we need to compute distances to
145 * \param[out] distances the resultant estimated distances
146 */
147 void
148 getDistancesToModel (const Eigen::VectorXf &model_coefficients,
149 std::vector<double> &distances) const override;
150
151 /** \brief Return a unique id for this model (SACMODEL_NORMAL_SPHERE). */
152 inline pcl::SacModel
153 getModelType () const override { return (SACMODEL_NORMAL_SPHERE); }
154
156
157 protected:
161 };
162}
163
164#ifdef PCL_NO_PRECOMPILE
165#include <pcl/sample_consensus/impl/sac_model_normal_sphere.hpp>
166#endif
PointCloud represents the base class in PCL for storing collections of 3D points.
Definition: point_cloud.h:173
SampleConsensusModelFromNormals represents the base model class for models that require the use of su...
Definition: sac_model.h:612
PointCloudNConstPtr normals_
A pointer to the input dataset that contains the point normals of the XYZ dataset.
Definition: sac_model.h:670
typename pcl::PointCloud< PointNT >::ConstPtr PointCloudNConstPtr
Definition: sac_model.h:614
typename pcl::PointCloud< PointNT >::Ptr PointCloudNPtr
Definition: sac_model.h:615
double normal_distance_weight_
The relative weight (between 0 and 1) to give to the angular distance (0 to pi/2) between point norma...
Definition: sac_model.h:665
SampleConsensusModel represents the base model class.
Definition: sac_model.h:70
double radius_min_
The minimum and maximum radius limits for the model.
Definition: sac_model.h:564
shared_ptr< SampleConsensusModel< PointT > > Ptr
Definition: sac_model.h:77
unsigned int sample_size_
The size of a sample from which the model is computed.
Definition: sac_model.h:588
typename PointCloud::ConstPtr PointCloudConstPtr
Definition: sac_model.h:73
IndicesPtr indices_
A pointer to the vector of point indices to use.
Definition: sac_model.h:556
PointCloudConstPtr input_
A boost shared pointer to the point cloud data array.
Definition: sac_model.h:553
std::string model_name_
The model name.
Definition: sac_model.h:550
unsigned int model_size_
The number of coefficients in the model.
Definition: sac_model.h:591
typename PointCloud::Ptr PointCloudPtr
Definition: sac_model.h:74
shared_ptr< const SampleConsensusModel< PointT > > ConstPtr
Definition: sac_model.h:78
std::vector< double > error_sqr_dists_
A vector holding the distances to the computed model.
Definition: sac_model.h:585
SampleConsensusModelNormalSphere defines a model for 3D sphere segmentation using additional surface ...
~SampleConsensusModelNormalSphere() override=default
Empty destructor.
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.
SampleConsensusModelNormalSphere(const PointCloudConstPtr &cloud, bool random=false)
Constructor for base SampleConsensusModelNormalSphere.
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 distances from the cloud data to a given sphere model.
pcl::SacModel getModelType() const override
Return a unique id for this model (SACMODEL_NORMAL_SPHERE).
SampleConsensusModelNormalSphere(const PointCloudConstPtr &cloud, const Indices &indices, bool random=false)
Constructor for base SampleConsensusModelNormalSphere.
SampleConsensusModelSphere defines a model for 3D sphere segmentation.
bool isModelValid(const Eigen::VectorXf &model_coefficients) const override
Check whether a model is valid given the user constraints.
#define PCL_MAKE_ALIGNED_OPERATOR_NEW
Macro to signal a class requires a custom allocator.
Definition: memory.h:63
Defines functions, macros and traits for allocating and using memory.
SacModel
Definition: model_types.h:46
@ SACMODEL_NORMAL_SPHERE
Definition: model_types.h:59
IndicesAllocator<> Indices
Type used for indices in PCL.
Definition: types.h:133
Defines all the PCL and non-PCL macros used.
A point structure representing Euclidean xyz coordinates, and the RGB color.