Point Cloud Library (PCL)  1.9.1-dev
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/common/common.h>
47 #include <pcl/pcl_macros.h>
48 
49 namespace 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 = boost::shared_ptr<SampleConsensusModelNormalSphere<PointT, PointNT> >;
89  using ConstPtr = boost::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 std::vector<int> &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  std::vector<int> &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  int
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:
160 
161  /** \brief Check whether a model is valid given the user constraints.
162  * \param[in] model_coefficients the set of model coefficients
163  */
164  bool
165  isModelValid (const Eigen::VectorXf &model_coefficients) const override;
166 
167  };
168 }
169 
170 #ifdef PCL_NO_PRECOMPILE
171 #include <pcl/sample_consensus/impl/sac_model_normal_sphere.hpp>
172 #endif
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.
bool isModelValid(const Eigen::VectorXf &model_coefficients) const override
Check whether a model is valid given the user constraints.
boost::shared_ptr< SampleConsensusModel< PointT > > Ptr
Definition: sac_model.h:76
This file defines compatibility wrappers for low level I/O functions.
Definition: convolution.h:45
unsigned int model_size_
The number of coefficients in the model.
Definition: sac_model.h:563
SampleConsensusModelNormalSphere defines a model for 3D sphere segmentation using additional surface ...
#define PCL_MAKE_ALIGNED_OPERATOR_NEW
Macro to signal a class requires a custom allocator.
Definition: pcl_macros.h:359
typename PointCloud::Ptr PointCloudPtr
Definition: sac_model.h:73
SampleConsensusModelNormalSphere(const PointCloudConstPtr &cloud, bool random=false)
Constructor for base SampleConsensusModelNormalSphere.
Define standard C methods and C++ classes that are common to all methods.
typename pcl::PointCloud< PointNT >::ConstPtr PointCloudNConstPtr
Definition: sac_model.h:582
SampleConsensusModel represents the base model class.
Definition: sac_model.h:68
boost::shared_ptr< const SampleConsensusModel< PointT > > ConstPtr
Definition: sac_model.h:77
std::string model_name_
The model name.
Definition: sac_model.h:522
pcl::SacModel getModelType() const override
Return a unique id for this model (SACMODEL_NORMAL_SPHERE).
typename PointCloud::ConstPtr PointCloudConstPtr
Definition: sac_model.h:72
SampleConsensusModelFromNormals represents the base model class for models that require the use of su...
Definition: sac_model.h:579
PointCloud represents the base class in PCL for storing collections of 3D points. ...
SacModel
Definition: model_types.h:45
int countWithinDistance(const Eigen::VectorXf &model_coefficients, const double threshold) const override
Count all the points which respect the given model coefficients as inliers.
A point structure representing Euclidean xyz coordinates, and the RGB color.
SampleConsensusModelNormalSphere(const PointCloudConstPtr &cloud, const std::vector< int > &indices, bool random=false)
Constructor for base SampleConsensusModelNormalSphere.
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.
typename pcl::PointCloud< PointNT >::Ptr PointCloudNPtr
Definition: sac_model.h:583
SampleConsensusModelSphere defines a model for 3D sphere segmentation.
Defines all the PCL and non-PCL macros used.
unsigned int sample_size_
The size of a sample from which the model is computed.
Definition: sac_model.h:560