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| Packages that use PointMatch | |
|---|---|
| mpi.cbg.fly | |
| Uses of PointMatch in mpi.cbg.fly |
|---|
| Methods in mpi.cbg.fly that return types with arguments of type PointMatch | |
|---|---|
static java.util.Vector<PointMatch> |
SIFT.createMatches(java.util.List<Feature> fs1,
java.util.List<Feature> fs2,
float max_sd,
Model model,
float max_id)
identify corresponding features using spatial constraints |
static java.util.ArrayList<PointMatch> |
PointMatch.flip(java.util.Collection<PointMatch> matches)
flip symmetrically, weight remains unchanged |
| Methods in mpi.cbg.fly with parameters of type PointMatch | |
|---|---|
boolean |
TRModel2D.fit(PointMatch[] min_matches)
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boolean |
TModel2D.fit(PointMatch[] min_matches)
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abstract boolean |
Model.fit(PointMatch[] min_matches)
fit the model to a minimal set of point correpondences estimates a model to transform match.p2.local to match.p1.world |
| Method parameters in mpi.cbg.fly with type arguments of type PointMatch | |
|---|---|
static TRModel2D |
TRModel2D.estimateBestModel(java.util.List<PointMatch> candidates,
java.util.Collection<PointMatch> inliers,
float min_epsilon,
float max_epsilon,
float min_inlier_ratio)
estimate the transformation model for a set of feature correspondences containing a high number of outliers using RANSAC increase the error as long as not more inliers occur |
static TRModel2D |
TRModel2D.estimateBestModel(java.util.List<PointMatch> candidates,
java.util.Collection<PointMatch> inliers,
float min_epsilon,
float max_epsilon,
float min_inlier_ratio)
estimate the transformation model for a set of feature correspondences containing a high number of outliers using RANSAC increase the error as long as not more inliers occur |
static TModel2D |
TModel2D.estimateBestModel(java.util.List<PointMatch> candidates,
java.util.Collection<PointMatch> inliers,
float min_epsilon,
float max_epsilon,
float min_inlier_ratio)
estimate the transformation model for a set of feature correspondences containing a high number of outliers using RANSAC increase the error as long as not more inliers occur |
static TModel2D |
TModel2D.estimateBestModel(java.util.List<PointMatch> candidates,
java.util.Collection<PointMatch> inliers,
float min_epsilon,
float max_epsilon,
float min_inlier_ratio)
estimate the transformation model for a set of feature correspondences containing a high number of outliers using RANSAC increase the error as long as not more inliers occur |
static TRModel2D |
TRModel2D.estimateModel(java.util.List<PointMatch> candidates,
java.util.Collection<PointMatch> inliers,
int iterations,
float epsilon,
float min_inlier_ratio)
estimate the transformation model for a set of feature correspondences containing a high number of outliers using RANSAC |
static TRModel2D |
TRModel2D.estimateModel(java.util.List<PointMatch> candidates,
java.util.Collection<PointMatch> inliers,
int iterations,
float epsilon,
float min_inlier_ratio)
estimate the transformation model for a set of feature correspondences containing a high number of outliers using RANSAC |
static TModel2D |
TModel2D.estimateModel(java.util.List<PointMatch> candidates,
java.util.Collection<PointMatch> inliers,
int iterations,
float epsilon,
float min_inliers)
estimate the transformation model for a set of feature correspondences containing a high number of outliers using RANSAC |
static TModel2D |
TModel2D.estimateModel(java.util.List<PointMatch> candidates,
java.util.Collection<PointMatch> inliers,
int iterations,
float epsilon,
float min_inliers)
estimate the transformation model for a set of feature correspondences containing a high number of outliers using RANSAC |
static java.util.ArrayList<PointMatch> |
PointMatch.flip(java.util.Collection<PointMatch> matches)
flip symmetrically, weight remains unchanged |
void |
TRModel2D.minimize(java.util.Collection<PointMatch> matches)
|
void |
TModel2D.minimize(java.util.Collection<PointMatch> matches)
|
abstract void |
Model.minimize(java.util.Collection<PointMatch> matches)
|
void |
TRModel2D.shake(java.util.Collection<PointMatch> matches,
float scale,
float[] center)
change the model a bit estimates the necessary amount of shaking for each single dimensional distance in the set of matches |
void |
TModel2D.shake(java.util.Collection<PointMatch> matches,
float scale,
float[] center)
change the model a bit estimates the necessary amount of shaking for each single dimensional distance in the set of matches |
abstract void |
Model.shake(java.util.Collection<PointMatch> matches,
float scale,
float[] center)
randomly change the model a bit estimates the necessary amount of shaking for each single dimensional distance in the set of matches |
boolean |
Model.test(java.util.Collection<PointMatch> candidates,
java.util.Collection<PointMatch> inliers,
double epsilon,
double min_inlier_ratio)
test the model for a set of point correspondence candidates clears inliers and fills it with the fitting subset of candidates |
boolean |
Model.test(java.util.Collection<PointMatch> candidates,
java.util.Collection<PointMatch> inliers,
double epsilon,
double min_inlier_ratio)
test the model for a set of point correspondence candidates clears inliers and fills it with the fitting subset of candidates |
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