Fit model to noisy data
[
fits
a model to noisy data using the M-estimator sample consensus (MSAC)
algorithm, a version of the random sample consensus (RANSAC) algorithm.model
,inlierIdx
]
= ransac(data
,fitFcn
,distFcn
,sampleSize
,maxDistance
)
Specify your function for fitting a model, fitFcn
,
and your function for calculating distances from the model to your
data, distFcn
. The ransac
function
takes random samples from your data
using sampleSize
and
uses the fit function to maximize the number of inliers within maxDistance
.
[___] = ransac(___,
additionally specifies one or more Name,Value
)Name,Value
pair
arguments.
[1] Torr, P. H. S., and A. Zisserman. "MLESAC: A New Robust Estimator with Application to Estimating Image Geometry." Computer Vision and Image Understanding. Vol. 18, Issue 1, April 2000, pp. 138–156.