ViSP
2.8.0

#include <vpRansac.h>
Static Public Member Functions  
static bool  ransac (unsigned int npts, vpColVector &x, unsigned int s, double t, vpColVector &model, vpColVector &inliers, int consensus=1000, double areaThreshold=0.0, const int maxNbumbersOfTrials=10000) 
This class is a generic implementation of the Ransac algorithm. It cannot be used alone.
Creation: june, 15 2005
RANSAC is described in :
M.A. Fishler and R.C. Boles. "Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography". Comm. Assoc. Comp, Mach., Vol 24, No 6, pp 381395, 1981
Richard Hartley and Andrew Zisserman. "Multiple View Geometry in Computer Vision". pp 101113. Cambridge University Press, 2001
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 93 of file vpRansac.h.

static 
RANSAC  Robustly fits a model to data with the RANSAC algorithm.
npts  : The number of data points. 
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. 
s  : The minimum number of samples from x required by fitting fn to fit a model. 
t  : The distance threshold between data point and the model used to decide whether a point is an inlier or not. 
M  : The model having the greatest number of inliers. 
inliers  : An array of indices of the elements of x that were the inliers for the best model. 
consensus  : Consensus 
areaThreshold  : Not used. 
maxNbumbersOfTrials  : Maximum number of trials. Even if a solution is not found, the method is stopped. 
Definition at line 138 of file vpRansac.h.
References vpException::fatalError, vpMath::maximum(), vpMath::minimum(), vpERROR_TRACE, and vpTRACE.
Referenced by vpPose::ransac(), and vpHomography::ransac().