Visual Servoing Platform
version 3.6.1 under development (20241112)

#include <visp3/core/vpRansac.h>
Static Public Member Functions  
static bool  ransac (unsigned int npts, const vpColVector &x, unsigned int s, double t, vpColVector &model, vpColVector &inliers, int consensus=1000, double not_used=0.0, int maxNbumbersOfTrials=10000, double *residual=nullptr) 
This class is a generic implementation of the Ransac algorithm. It cannot be used alone.
RANSAC is described in [15] and [19].
The code of this class is inspired by : Peter Kovesi School of Computer Science & Software Engineering The University of Western Australia pk at csse uwa edu au http://www.csse.uwa.edu.au/~pk
Definition at line 66 of file vpRansac.h.

static 
RANSAC  Robustly fits a model to data with the RANSAC algorithm.
[in]  npts  : The number of data points. 
[in]  x  : Data sets to which we are seeking to fit a model M. It is assumed that x is of size [d x Npts] where d is the dimensionality of the data and npts is the number of data points. 
[in]  s  : The minimum number of samples from x required by fitting fn to fit a model. Value should be greater or equal to 4. 
[in]  t  : The distance threshold between data point and the model used to decide whether a point is an inlier or not. 
[out]  M  : The model having the greatest number of inliers. 
[out]  inliers  : An array of indices of the elements of x that were the inliers for the best model. 
[in]  consensus  : Consensus 
[in]  not_used  : Unused parameter. 
[in]  maxNbumbersOfTrials  : Maximum number of trials. Even if a solution is not found, the method is stopped. 
[out]  residual  : Residual 
Definition at line 107 of file vpRansac.h.
References vpException::fatalError, vpMath::maximum(), and vpMath::minimum().