[−]Trait cv::sample_consensus::MultiConsensus
See Consensus
. A multi-consensus can handle situations where different subsets of the data are consistent
with different models. This kind of consensus also considers whether a point is part of another orthogonal
model that is known before assuming it is a true outlier. In this situation there are inliers of different
models and then true outliers that are actual erroneous data that should be filtered out.
Associated Types
type Inliers: IntoIterator
Iterator over the indices of the inliers in the clonable iterator.
type Models: IntoIterator
Required methods
fn models<I>(&mut self, estimator: &E, data: I) -> Self::Models where
I: Iterator<Item = Data> + Clone,
I: Iterator<Item = Data> + Clone,
Takes a slice over the data and an estimator instance. It returns an iterator over all of the models and all of the inliers that are consistent with that model. Every point that is not an inlier of a given model is considered an outlier of that model.