| Package | Description |
|---|---|
| org.openimaj.math.geometry.transforms.estimation | |
| org.openimaj.math.model.fit |
| Constructor and Description |
|---|
RobustAffineTransformEstimator(double threshold,
int nIterations,
RANSAC.StoppingCondition stoppingCondition)
Construct using the
RANSAC algorithm with the given options. |
RobustAffineTransformEstimator(double threshold,
int nIterations,
RANSAC.StoppingCondition stoppingCondition,
Predicate<AffineTransformModel> modelCheck)
Construct using the
RANSAC algorithm with the given options. |
RobustFundamentalEstimator(double threshold,
int nIterations,
RANSAC.StoppingCondition stoppingCondition,
FundamentalRefinement refinement)
Construct using the
RANSAC algorithm with the given options. |
RobustHomographyEstimator(double threshold,
int nIterations,
RANSAC.StoppingCondition stoppingCondition,
HomographyRefinement refinement)
Construct using the
RANSAC algorithm with the given options. |
RobustHomographyEstimator(double threshold,
int nIterations,
RANSAC.StoppingCondition stoppingCondition,
HomographyRefinement refinement,
Predicate<HomographyModel> modelCheck)
Construct using the
RANSAC algorithm with the given options. |
| Modifier and Type | Class and Description |
|---|---|
static class |
RANSAC.BestFitStoppingCondition
Stopping condition that allows the RANSAC algorithm to run until all the
iterations have been exhausted.
|
static class |
RANSAC.NumberInliersStoppingCondition
Stopping condition that tests the number of matches against a threshold.
|
static class |
RANSAC.PercentageInliersStoppingCondition
Stopping condition that tests the number of matches against a percentage
threshold of the whole data.
|
static class |
RANSAC.ProbabilisticMinInliersStoppingCondition
Stopping condition that tests the number of matches against a percentage
threshold of the whole data.
|
| Modifier and Type | Field and Description |
|---|---|
protected RANSAC.StoppingCondition |
RANSAC.stoppingCondition |
| Constructor and Description |
|---|
RANSAC(M model,
ResidualCalculator<I,D,M> errorModel,
DistanceCheck dc,
int nIterations,
RANSAC.StoppingCondition stoppingCondition,
boolean impEst)
Create a RANSAC object with uniform random sampling for creating the
subsets
|
RANSAC(M model,
ResidualCalculator<I,D,M> errorModel,
DistanceCheck dc,
int nIterations,
RANSAC.StoppingCondition stoppingCondition,
boolean impEst,
CollectionSampler<IndependentPair<I,D>> sampler)
Create a RANSAC object
|
RANSAC(M model,
ResidualCalculator<I,D,M> errorModel,
double errorThreshold,
int nIterations,
RANSAC.StoppingCondition stoppingCondition,
boolean impEst)
Create a RANSAC object with uniform random sampling for creating the
subsets
|
RANSAC(M model,
ResidualCalculator<I,D,M> errorModel,
double errorThreshold,
int nIterations,
RANSAC.StoppingCondition stoppingCondition,
boolean impEst,
CollectionSampler<IndependentPair<I,D>> sampler)
Create a RANSAC object
|