40 #ifndef PCL_SEGMENTATION_SAC_SEGMENTATION_H_
41 #define PCL_SEGMENTATION_SAC_SEGMENTATION_H_
43 #include <pcl/pcl_base.h>
44 #include <pcl/PointIndices.h>
45 #include <pcl/ModelCoefficients.h>
48 #include <pcl/sample_consensus/method_types.h>
49 #include <pcl/sample_consensus/sac.h>
51 #include <pcl/sample_consensus/model_types.h>
52 #include <pcl/sample_consensus/sac_model.h>
54 #include <pcl/search/search.h>
64 template <
typename Po
intT>
92 ,
radius_min_ (-std::numeric_limits<double>::max ())
97 ,
axis_ (Eigen::Vector3f::Zero ())
225 inline Eigen::Vector3f
256 initSAC (
const int method_type);
309 template <
typename Po
intT,
typename Po
intNT>
427 #ifdef PCL_NO_PRECOMPILE
428 #include <pcl/segmentation/impl/sac_segmentation.hpp>
431 #endif //#ifndef PCL_SEGMENTATION_SAC_SEGMENTATION_H_
void setMaxIterations(int max_iterations)
Set the maximum number of iterations before giving up.
pcl::search::Search< PointT >::Ptr SearchPtr
double distance_weight_
The relative weight (between 0 and 1) to give to the angular distance (0 to pi/2) between point norma...
void setMethodType(int method)
The type of sample consensus method to use (user given parameter).
double distance_from_origin_
The distance from the template plane to the origin.
virtual std::string getClassName() const
Class get name method.
PointCloudNConstPtr normals_
A pointer to the input dataset that contains the point normals of the XYZ dataset.
SACSegmentation represents the Nodelet segmentation class for Sample Consensus methods and models...
int getModelType() const
Get the type of SAC model used.
SACSegmentation(bool random=false)
Empty constructor.
SampleConsensusModelPtr getModel() const
Get a pointer to the SAC model used.
SampleConsensusPtr getMethod() const
Get a pointer to the SAC method used.
double min_angle_
The minimum and maximum allowed opening angle of valid cone model.
void setSamplesMaxDist(const double &radius, SearchPtr search)
Set the maximum distance allowed when drawing random samples.
double getDistanceThreshold() const
Get the distance to the model threshold.
int max_iterations_
Maximum number of iterations before giving up (user given parameter).
void setMinMaxOpeningAngle(const double &min_angle, const double &max_angle)
Set the minimum opning angle for a cone model.
PointCloud::Ptr PointCloudPtr
virtual ~SACSegmentation()
Empty destructor.
bool getOptimizeCoefficients() const
Get the coefficient refinement internal flag.
double threshold_
Distance to the model threshold (user given parameter).
double samples_radius_
The maximum distance of subsequent samples from the first (radius search)
bool optimize_coefficients_
Set to true if a coefficient refinement is required.
virtual bool initSACModel(const int model_type)
Initialize the Sample Consensus model and set its parameters.
PointCloud::Ptr PointCloudPtr
SampleConsensusModel< PointT >::Ptr SampleConsensusModelPtr
void setDistanceFromOrigin(const double d)
Set the distance we expect a plane model to be from the origin.
SampleConsensusModelPtr model_
The model that needs to be segmented.
double eps_angle_
The maximum allowed difference between the model normal and the given axis.
PointCloud::ConstPtr PointCloudConstPtr
PointCloud::ConstPtr PointCloudConstPtr
PointCloudN::Ptr PointCloudNPtr
int method_type_
The type of sample consensus method to use (user given parameter).
void setAxis(const Eigen::Vector3f &ax)
Set the axis along which we need to search for a model perpendicular to.
SampleConsensus< PointT >::Ptr SampleConsensusPtr
void setOptimizeCoefficients(bool optimize)
Set to true if a coefficient refinement is required.
void setModelType(int model)
The type of model to use (user given parameter).
double getEpsAngle() const
Get the epsilon (delta) model angle threshold in radians.
Eigen::Vector3f axis_
The axis along which we need to search for a model perpendicular to.
pcl::PointCloud< PointT > PointCloud
void setInputNormals(const PointCloudNConstPtr &normals)
Provide a pointer to the input dataset that contains the point normals of the XYZ dataset...
double probability_
Desired probability of choosing at least one sample free from outliers (user given parameter)...
void setDistanceThreshold(double threshold)
Distance to the model threshold (user given parameter).
SampleConsensusModelFromNormals< PointT, PointNT >::Ptr SampleConsensusModelFromNormalsPtr
double radius_min_
The minimum and maximum radius limits for the model.
SampleConsensus represents the base class.
int getMethodType() const
Get the type of sample consensus method used.
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...
boost::shared_ptr< pcl::search::Search< PointT > > Ptr
PointCloudN::ConstPtr PointCloudNConstPtr
SACSegmentationFromNormals(bool random=false)
Empty constructor.
virtual std::string getClassName() const
Class get name method.
void setNormalDistanceWeight(double distance_weight)
Set the relative weight (between 0 and 1) to give to the angular distance (0 to pi/2) between point n...
SampleConsensusModel< PointT >::Ptr SampleConsensusModelPtr
boost::shared_ptr< PointCloud< PointT > > Ptr
void getMinMaxOpeningAngle(double &min_angle, double &max_angle)
Get the opening angle which we need minumum to validate a cone model.
PointCloudNConstPtr getInputNormals() const
Get a pointer to the normals of the input XYZ point cloud dataset.
virtual void segment(PointIndices &inliers, ModelCoefficients &model_coefficients)
Base method for segmentation of a model in a PointCloud given by <setInputCloud (), setIndices ()>
bool random_
Set to true if we need a random seed.
boost::shared_ptr< const PointCloud< PointT > > ConstPtr
boost::shared_ptr< SampleConsensusModelFromNormals > Ptr
virtual void initSAC(const int method_type)
Initialize the Sample Consensus method and set its parameters.
SampleConsensusPtr sac_
The sample consensus segmentation method.
virtual bool initSACModel(const int model_type)
Initialize the Sample Consensus model and set its parameters.
void getRadiusLimits(double &min_radius, double &max_radius)
Get the minimum and maximum allowable radius limits for the model as set by the user.
void setEpsAngle(double ea)
Set the angle epsilon (delta) threshold.
void getSamplesMaxDist(double &radius)
Get maximum distance allowed when drawing random samples.
void setProbability(double probability)
Set the probability of choosing at least one sample free from outliers.
SACSegmentation< PointT >::PointCloud PointCloud
SampleConsensus< PointT >::Ptr SampleConsensusPtr
Eigen::Vector3f getAxis() const
Get the axis along which we need to search for a model perpendicular to.
SACSegmentationFromNormals represents the PCL nodelet segmentation class for Sample Consensus methods...
double getDistanceFromOrigin() const
Get the distance of a plane model from the origin.
boost::shared_ptr< SampleConsensusModel > Ptr
double getProbability() const
Get the probability of choosing at least one sample free from outliers.
A point structure representing Euclidean xyz coordinates, and the RGB color.
pcl::PointCloud< PointNT > PointCloudN
SearchPtr samples_radius_search_
The search object for picking subsequent samples using radius search.
int getMaxIterations() const
Get maximum number of iterations before giving up.
double getNormalDistanceWeight() const
Get the relative weight (between 0 and 1) to give to the angular distance (0 to pi/2) between point n...
int model_type_
The type of model to use (user given parameter).