feature.RANSAC

RANdom SAmple Consensus

Martin A. Fischler and Robert C. Bolles, “Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography”, Communications of the ACM, 1981

IModel

class supreme.feature.RANSAC.IModel

This class defines the structure for a model.

Attributes

parameters
ndp

Methods

estimate(data)

Estimate model parameters from data.

estimate(data)

Estimate model parameters from data.

Parameters:

data : array

Data points as row vectors.

Returns:

parameters: :

Model parameters in any format the model can interpret.

residual : float

Measure of data fit.

RANSAC

class supreme.feature.RANSAC.RANSAC(model=None, p_inlier=None)

Bases: object

RANdom SAmple Consensus

__init__(model=None, p_inlier=None)

Parameters:

model : Model

Model describing inlier data.

p_inlier : float (0..1)

Probability that any data point is an inlier.