#include <sac.h>
Public Member Functions | |
| virtual void | computeCoefficients (std::vector< double > &coefficients) |
| Compute the coefficients of the model and return them. | |
| virtual bool | computeModel (int debug=0)=0 |
| Compute the actual model. Pure virtual. | |
| virtual std::vector< int > | getInliers () |
| Get a list of the model inliers, found after computeModel (). | |
| sensor_msgs::PointCloud | getPointCloud (std::vector< int > indices) |
| Return the point cloud representing a set of given indices. | |
| std::set< int > | getRandomSamples (sensor_msgs::PointCloud points, std::vector< int > indices, int nr_samples) |
| Get a vector of randomly selected indices. | |
| std::set< int > | getRandomSamples (sensor_msgs::PointCloud points, int nr_samples) |
| Get a set of randomly selected indices. | |
| virtual void | projectPointsToModel (const std::vector< int > &indices, const std::vector< double > &model_coefficients, sensor_msgs::PointCloud &projected_points) |
| Project a set of given points (using their indices) onto the model and return their projections. | |
| virtual void | refineCoefficients (std::vector< double > &refined_coefficients) |
| Use Least-Squares optimizations to refine the coefficients of the model, and return them. | |
| virtual int | removeInliers () |
| Remove the model inliers from the list of data indices. Returns the number of indices left. | |
| SAC (SACModel *model) | |
| Constructor for base SAC. | |
| SAC () | |
| Constructor for base SAC. | |
| virtual void | setMaxIterations (int max_iterations) |
| Set the maximum number of iterations. | |
| virtual void | setProbability (double probability) |
| Set the desired probability of choosing at least one sample free from outliers. | |
| virtual void | setThreshold (double threshold) |
| Set the threshold to model. | |
| virtual | ~SAC () |
| Destructor for base SAC. | |
Protected Attributes | |
| int | iterations_ |
| Total number of internal loop iterations that we've done so far. | |
| int | max_iterations_ |
| Maximum number of iterations before giving up. | |
| double | probability_ |
| Desired probability of choosing at least one sample free from outliers. | |
| SACModel * | sac_model_ |
| The underlying data model used (i.e. what is it that we attempt to search for). | |
| double | threshold_ |
| Distance to model threshold. | |
Definition at line 44 of file sac.h.
| sample_consensus::SAC::SAC | ( | ) | [inline] |
| sample_consensus::SAC::SAC | ( | SACModel * | model | ) | [inline] |
| virtual sample_consensus::SAC::~SAC | ( | ) | [inline, virtual] |
| virtual void sample_consensus::SAC::computeCoefficients | ( | std::vector< double > & | coefficients | ) | [inline, virtual] |
| virtual bool sample_consensus::SAC::computeModel | ( | int | debug = 0 |
) | [pure virtual] |
Compute the actual model. Pure virtual.
Implemented in sample_consensus::LMedS, sample_consensus::MLESAC, sample_consensus::MSAC, sample_consensus::RANSAC, sample_consensus::RMSAC, and sample_consensus::RRANSAC.
| virtual std::vector<int> sample_consensus::SAC::getInliers | ( | ) | [inline, virtual] |
| sensor_msgs::PointCloud SAC::getPointCloud | ( | std::vector< int > | indices | ) |
| std::set<int> sample_consensus::SAC::getRandomSamples | ( | sensor_msgs::PointCloud | points, | |
| std::vector< int > | indices, | |||
| int | nr_samples | |||
| ) | [inline] |
Get a vector of randomly selected indices.
| points | the point cloud data set to be used (unused) | |
| indices | a set of indices that represent the data that we're interested in | |
| nr_samples | the desired number of point indices |
| std::set<int> sample_consensus::SAC::getRandomSamples | ( | sensor_msgs::PointCloud | points, | |
| int | nr_samples | |||
| ) | [inline] |
Get a set of randomly selected indices.
| points | the point cloud data set to be used | |
| nr_samples | the desired number of point indices |
| virtual void sample_consensus::SAC::projectPointsToModel | ( | const std::vector< int > & | indices, | |
| const std::vector< double > & | model_coefficients, | |||
| sensor_msgs::PointCloud & | projected_points | |||
| ) | [inline, virtual] |
Project a set of given points (using their indices) onto the model and return their projections.
| indices | a set of indices that represent the data that we're interested in | |
| model_coefficients | the coefficients of the underlying model | |
| projected_points | the resultant projected points |
| virtual void sample_consensus::SAC::refineCoefficients | ( | std::vector< double > & | refined_coefficients | ) | [inline, virtual] |
| virtual int sample_consensus::SAC::removeInliers | ( | ) | [inline, virtual] |
| virtual void sample_consensus::SAC::setMaxIterations | ( | int | max_iterations | ) | [inline, virtual] |
| virtual void sample_consensus::SAC::setProbability | ( | double | probability | ) | [inline, virtual] |
| virtual void sample_consensus::SAC::setThreshold | ( | double | threshold | ) | [inline, virtual] |
int sample_consensus::SAC::iterations_ [protected] |
int sample_consensus::SAC::max_iterations_ [protected] |
double sample_consensus::SAC::probability_ [protected] |
SACModel* sample_consensus::SAC::sac_model_ [protected] |
double sample_consensus::SAC::threshold_ [protected] |
