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RandomSampleConsensus Class

Class implementing the Random Sample Consensus (RANSAC) algorithm for a generic data type.
RANSAC is an iterative non-deterministic algorithm used for fitting estimation in the presence of a large number of outliers in the data.

Constructors

RandomSampleConsensus ( dataPoints , exclusionZone )
Initializes a new instance of the RandomSampleConsensus class.
Signature 
Oculus.Interaction.RandomSampleConsensus< TModel >.RandomSampleConsensus(int dataPoints=8, int exclusionZone=2)
Parameters
dataPoints: int  The total number of sample points.
exclusionZone: int  The threshold to avoid selecting samples too close to each other.

Methods

EvaluateModelScore ( model , modelSet )
Delegate for evaluating the agreement score of a model with respect to the entire dataset.
Signature 
delegate float Oculus.Interaction.RandomSampleConsensus< TModel >.EvaluateModelScore(TModel model, TModel[,] modelSet)
Parameters
model: TModel  The model to be evaluated.
modelSet: TModel  The set of all generated models for comparison.
Returns
delegate float  The score representing the model's agreement with the data.
FindOptimalModel ( modelGenerator , modelScorer )
Calculates the best fitting model based on the RANSAC algorithm.
Signature 
TModel Oculus.Interaction.RandomSampleConsensus< TModel >.FindOptimalModel(GenerateModel modelGenerator, EvaluateModelScore modelScorer)
Parameters
modelGenerator: GenerateModel  The function to generate models from data points.
modelScorer: EvaluateModelScore  The function to evaluate the agreement score of a model.
Returns
TModel  The model that best fits the data according to the RANSAC algorithm.
GenerateModel ( index1 , index2 )
Delegate for generating a model from a pair of samples, represented by their indices.
Signature 
delegate TModel Oculus.Interaction.RandomSampleConsensus< TModel >.GenerateModel(int index1, int index2)
Parameters
index1: int  The first sample index.
index2: int  The second sample index.
Returns
delegate TModel  A model generated from the provided indices.
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