public class ConstantModel<A extends Model<A>,M extends ConstantModel<A,M>> extends AbstractModel<M>
Model.fit(float[][], float[][], float[]).
We use this to let models influence each other combining them in an
InterpolatedModel.| Modifier and Type | Field and Description |
|---|---|
protected A |
model |
cost, rnd| Constructor and Description |
|---|
ConstantModel(A model) |
| Modifier and Type | Method and Description |
|---|---|
double[] |
apply(double[] location)
Apply the
CoordinateTransform to a location. |
void |
applyInPlace(double[] location)
Apply the
CoordinateTransform to a location. |
M |
copy()
Clone the model.
|
<P extends PointMatch> |
fit(Collection<P> matches)
Fit the
Model to a set of data points minimizing the global
transfer error. |
int |
getMinNumMatches() |
A |
getModel() |
void |
set(M m)
Set the model to m
|
betterThan, filter, filter, filter, filterRansac, filterRansac, filterRansac, filterRansac, fit, fit, getCost, icp, localSmoothnessFilter, ransac, ransac, setCost, test, testpublic ConstantModel(A model)
public A getModel()
public int getMinNumMatches()
PointMatches required
to solve the model.public <P extends PointMatch> void fit(Collection<P> matches)
ModelModel to a set of data points minimizing the global
transfer error. This is assumed to be implemented as a weighted least
squares minimization. Use ransac
and/ or Model.filter(java.util.Collection<P>, java.util.Collection<P>, double, int) to remove outliers from your data points.
The estimated model transfers match.p1.local to match.p2.world.
matches - set of point correpondencespublic double[] apply(double[] location)
CoordinateTransformCoordinateTransform to a location.public void applyInPlace(double[] location)
CoordinateTransformCoordinateTransform to a location.Copyright © 2015–2021 Fiji. All rights reserved.