SampleConsensusModelNormalSphere defines a model for 3D sphere segmentation using additional surface normal constraints. More...
#include <pcl/sample_consensus/sac_model_normal_sphere.h>
Public Member Functions | |
SampleConsensusModelNormalSphere (const PointCloudConstPtr &cloud, bool random=false) | |
Constructor for base SampleConsensusModelNormalSphere. More... |
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SampleConsensusModelNormalSphere (const PointCloudConstPtr &cloud, const Indices &indices, bool random=false) | |
Constructor for base SampleConsensusModelNormalSphere. More... |
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~SampleConsensusModelNormalSphere () | |
Empty destructor. More... |
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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. More... |
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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. More... |
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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. More... |
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pcl::SacModel | getModelType () const override |
Return a unique id for this model (SACMODEL_NORMAL_SPHERE). More... |
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Public Member Functions inherited from pcl::SampleConsensusModelSphere< PointT > | |
SampleConsensusModelSphere (const PointCloudConstPtr &cloud, bool random=false) | |
Constructor for base SampleConsensusModelSphere. More... |
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SampleConsensusModelSphere (const PointCloudConstPtr &cloud, const Indices &indices, bool random=false) | |
Constructor for base SampleConsensusModelSphere. More... |
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~SampleConsensusModelSphere () | |
Empty destructor. More... |
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SampleConsensusModelSphere (const SampleConsensusModelSphere &source) | |
Copy constructor. More... |
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SampleConsensusModelSphere & | operator= (const SampleConsensusModelSphere &source) |
Copy constructor. More... |
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bool | computeModelCoefficients (const Indices &samples, Eigen::VectorXf &model_coefficients) const override |
Check whether the given index samples can form a valid sphere model, compute the model coefficients from these samples and store them internally in model_coefficients. More... |
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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. More... |
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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. More... |
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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. More... |
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void | optimizeModelCoefficients (const Indices &inliers, const Eigen::VectorXf &model_coefficients, Eigen::VectorXf &optimized_coefficients) const override |
Recompute the sphere coefficients using the given inlier set and return them to the user. More... |
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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 sphere model. More... |
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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 sphere model coefficients. More... |
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pcl::SacModel | getModelType () const override |
Return a unique id for this model (SACMODEL_SPHERE). More... |
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Public Member Functions inherited from pcl::SampleConsensusModel< PointT > | |
SampleConsensusModel (const PointCloudConstPtr &cloud, bool random=false) | |
Constructor for base SampleConsensusModel. More... |
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SampleConsensusModel (const PointCloudConstPtr &cloud, const Indices &indices, bool random=false) | |
Constructor for base SampleConsensusModel. More... |
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virtual | ~SampleConsensusModel () |
Destructor for base SampleConsensusModel. More... |
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virtual void | getSamples (int &iterations, Indices &samples) |
Get a set of random data samples and return them as point indices. More... |
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virtual void | setInputCloud (const PointCloudConstPtr &cloud) |
Provide a pointer to the input dataset. More... |
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PointCloudConstPtr | getInputCloud () const |
Get a pointer to the input point cloud dataset. More... |
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void | setIndices (const IndicesPtr &indices) |
Provide a pointer to the vector of indices that represents the input data. More... |
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void | setIndices (const Indices &indices) |
Provide the vector of indices that represents the input data. More... |
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IndicesPtr | getIndices () const |
Get a pointer to the vector of indices used. More... |
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const std::string & | getClassName () const |
Get a string representation of the name of this class. More... |
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unsigned int | getSampleSize () const |
Return the size of a sample from which the model is computed. More... |
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unsigned int | getModelSize () const |
Return the number of coefficients in the model. More... |
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void | setRadiusLimits (const double &min_radius, const double &max_radius) |
Set the minimum and maximum allowable radius limits for the model (applicable to models that estimate a radius) More... |
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void | getRadiusLimits (double &min_radius, double &max_radius) const |
Get the minimum and maximum allowable radius limits for the model as set by the user. More... |
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void | setModelConstraints (std::function< bool(const Eigen::VectorXf &)> function) |
This can be used to impose any kind of constraint on the model, e.g. More... |
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void | setSamplesMaxDist (const double &radius, SearchPtr search) |
Set the maximum distance allowed when drawing random samples. More... |
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void | getSamplesMaxDist (double &radius) const |
Get maximum distance allowed when drawing random samples. More... |
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double | computeVariance (const std::vector< double > &error_sqr_dists) const |
Compute the variance of the errors to the model. More... |
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double | computeVariance () const |
Compute the variance of the errors to the model from the internally estimated vector of distances. More... |
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Public Member Functions inherited from pcl::SampleConsensusModelFromNormals< PointT, PointNT > | |
SampleConsensusModelFromNormals () | |
Empty constructor for base SampleConsensusModelFromNormals. More... |
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virtual | ~SampleConsensusModelFromNormals () |
Destructor. More... |
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void | setNormalDistanceWeight (const double w) |
Set the normal angular distance weight. More... |
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double | getNormalDistanceWeight () const |
Get the normal angular distance weight. More... |
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void | setInputNormals (const PointCloudNConstPtr &normals) |
Provide a pointer to the input dataset that contains the point normals of the XYZ dataset. More... |
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PointCloudNConstPtr | getInputNormals () const |
Get a pointer to the normals of the input XYZ point cloud dataset. More... |
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Additional Inherited Members | |
Protected Member Functions inherited from pcl::SampleConsensusModelSphere< PointT > | |
bool | isModelValid (const Eigen::VectorXf &model_coefficients) const override |
Check whether a model is valid given the user constraints. More... |
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bool | isSampleGood (const Indices &samples) const override |
Check if a sample of indices results in a good sample of points indices. More... |
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std::size_t | countWithinDistanceStandard (const Eigen::VectorXf &model_coefficients, const double threshold, std::size_t i=0) const |
This implementation uses no SIMD instructions. More... |
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Protected Member Functions inherited from pcl::SampleConsensusModel< PointT > | |
SampleConsensusModel (bool random=false) | |
Empty constructor for base SampleConsensusModel. More... |
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void | drawIndexSample (Indices &sample) |
Fills a sample array with random samples from the indices_ vector. More... |
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void | drawIndexSampleRadius (Indices &sample) |
Fills a sample array with one random sample from the indices_ vector and other random samples that are closer than samples_radius_. More... |
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int | rnd () |
Boost-based random number generator. More... |
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Protected Attributes inherited from pcl::SampleConsensusModel< PointT > | |
std::string | model_name_ |
The model name. More... |
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PointCloudConstPtr | input_ |
A boost shared pointer to the point cloud data array. More... |
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IndicesPtr | indices_ |
A pointer to the vector of point indices to use. More... |
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double | radius_min_ |
The minimum and maximum radius limits for the model. More... |
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double | radius_max_ |
double | samples_radius_ |
The maximum distance of subsequent samples from the first (radius search) More... |
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SearchPtr | samples_radius_search_ |
The search object for picking subsequent samples using radius search. More... |
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Indices | shuffled_indices_ |
Data containing a shuffled version of the indices. More... |
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boost::mt19937 | rng_alg_ |
Boost-based random number generator algorithm. More... |
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std::shared_ptr< boost::uniform_int<> > | rng_dist_ |
Boost-based random number generator distribution. More... |
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std::shared_ptr< boost::variate_generator< boost::mt19937 &, boost::uniform_int<> > > | rng_gen_ |
Boost-based random number generator. More... |
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std::vector< double > | error_sqr_dists_ |
A vector holding the distances to the computed model. More... |
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unsigned int | sample_size_ |
The size of a sample from which the model is computed. More... |
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unsigned int | model_size_ |
The number of coefficients in the model. More... |
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std::function< bool(const Eigen::VectorXf &)> | custom_model_constraints_ |
A user defined function that takes model coefficients and returns whether the model is acceptable or not. More... |
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Protected Attributes inherited from pcl::SampleConsensusModelFromNormals< PointT, PointNT > | |
double | normal_distance_weight_ |
The relative weight (between 0 and 1) to give to the angular distance (0 to pi/2) between point normals and the plane normal. More... |
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PointCloudNConstPtr | normals_ |
A pointer to the input dataset that contains the point normals of the XYZ dataset. More... |
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Static Protected Attributes inherited from pcl::SampleConsensusModel< PointT > | |
static const unsigned int | max_sample_checks_ = 1000 |
The maximum number of samples to try until we get a good one. More... |
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SampleConsensusModelNormalSphere defines a model for 3D sphere segmentation using additional surface normal constraints.
Basically this means that checking for inliers will not only involve a "distance to model" criterion, but also an additional "maximum angular deviation" between the sphere's normal and the inlier points normals.
The model coefficients are defined as:
Definition at line 69 of file sac_model_normal_sphere.h.
using pcl::SampleConsensusModelNormalSphere< PointT, PointNT >::ConstPtr = shared_ptr<const SampleConsensusModelNormalSphere<PointT, PointNT> > |
Definition at line 89 of file sac_model_normal_sphere.h.
using pcl::SampleConsensusModelNormalSphere< PointT, PointNT >::PointCloud = typename SampleConsensusModel<PointT>::PointCloud |
Definition at line 81 of file sac_model_normal_sphere.h.
using pcl::SampleConsensusModelNormalSphere< PointT, PointNT >::PointCloudConstPtr = typename SampleConsensusModel<PointT>::PointCloudConstPtr |
Definition at line 83 of file sac_model_normal_sphere.h.
using pcl::SampleConsensusModelNormalSphere< PointT, PointNT >::PointCloudNConstPtr = typename SampleConsensusModelFromNormals<PointT, PointNT>::PointCloudNConstPtr |
Definition at line 86 of file sac_model_normal_sphere.h.
using pcl::SampleConsensusModelNormalSphere< PointT, PointNT >::PointCloudNPtr = typename SampleConsensusModelFromNormals<PointT, PointNT>::PointCloudNPtr |
Definition at line 85 of file sac_model_normal_sphere.h.
using pcl::SampleConsensusModelNormalSphere< PointT, PointNT >::PointCloudPtr = typename SampleConsensusModel<PointT>::PointCloudPtr |
Definition at line 82 of file sac_model_normal_sphere.h.
using pcl::SampleConsensusModelNormalSphere< PointT, PointNT >::Ptr = shared_ptr<SampleConsensusModelNormalSphere<PointT, PointNT> > |
Definition at line 88 of file sac_model_normal_sphere.h.
| inline |
Constructor for base SampleConsensusModelNormalSphere.
[in] | cloud | the input point cloud dataset |
[in] | random | if true set the random seed to the current time, else set to 12345 (default: false) |
Definition at line 95 of file sac_model_normal_sphere.h.
References pcl::SampleConsensusModel< PointT >::model_name_, pcl::SampleConsensusModel< PointT >::model_size_, and pcl::SampleConsensusModel< PointT >::sample_size_.
| inline |
Constructor for base SampleConsensusModelNormalSphere.
[in] | cloud | the input point cloud dataset |
[in] | indices | a vector of point indices to be used from cloud |
[in] | random | if true set the random seed to the current time, else set to 12345 (default: false) |
Definition at line 110 of file sac_model_normal_sphere.h.
References pcl::SampleConsensusModel< PointT >::model_name_, pcl::SampleConsensusModel< PointT >::model_size_, and pcl::SampleConsensusModel< PointT >::sample_size_.
| inline |
Empty destructor.
Definition at line 122 of file sac_model_normal_sphere.h.
| overridevirtual |
Count all the points which respect the given model coefficients as inliers.
[in] | model_coefficients | the coefficients of a model that we need to compute distances to |
[in] | threshold | maximum admissible distance threshold for determining the inliers from the outliers |
Implements pcl::SampleConsensusModel< PointT >.
Definition at line 110 of file sac_model_normal_sphere.hpp.
References pcl::getAngle3D(), and M_PI.
| overridevirtual |
Compute all distances from the cloud data to a given sphere model.
[in] | model_coefficients | the coefficients of a sphere model that we need to compute distances to |
[out] | distances | the resultant estimated distances |
Implements pcl::SampleConsensusModel< PointT >.
Definition at line 161 of file sac_model_normal_sphere.hpp.
References pcl::getAngle3D(), and M_PI.
| inlineoverridevirtual |
Return a unique id for this model (SACMODEL_NORMAL_SPHERE).
Implements pcl::SampleConsensusModel< PointT >.
Definition at line 153 of file sac_model_normal_sphere.h.
References pcl::SACMODEL_NORMAL_SPHERE.
| overridevirtual |
Select all the points which respect the given model coefficients as inliers.
[in] | model_coefficients | the coefficients of a sphere model that we need to compute distances to |
[in] | threshold | a maximum admissible distance threshold for determining the inliers from the outliers |
[out] | inliers | the resultant model inliers |
Implements pcl::SampleConsensusModel< PointT >.
Definition at line 49 of file sac_model_normal_sphere.hpp.
References pcl::geometry::distance(), pcl::getAngle3D(), and M_PI.
© 2009–2012, Willow Garage, Inc.
© 2012–, Open Perception, Inc.
Licensed under the BSD License.
https://pointclouds.org/documentation/classpcl_1_1_sample_consensus_model_normal_sphere.html