Package | Description |
---|---|
stitching | |
stitching.model |
Constructor and Description |
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ImageInformation(int dim,
int id,
Model model) |
Modifier and Type | Class and Description |
---|---|
class |
InvertibleModel
TODO
|
class |
TranslationModel2D
TODO
|
class |
TranslationModel3D
TODO
|
Modifier and Type | Method and Description |
---|---|
static <M extends Model> |
Model.filter(Class<M> modelClass,
Collection<PointMatch> candidates,
Collection<PointMatch> inliers)
Estimate a
Model and filter potential outliers by robust
iterative regression. |
static <M extends Model> |
Model.filterRansac(Class<M> modelType,
List<PointMatch> candidates,
Collection<PointMatch> inliers,
int iterations,
float max_epsilon,
float min_inlier_ratio)
Estimate the best model for a set of feature correspondence candidates.
|
static <M extends Model> |
Model.ransac(Class<M> modelClass,
List<PointMatch> candidates,
Collection<PointMatch> inliers,
int iterations,
double epsilon,
double min_inlier_ratio)
|
Modifier and Type | Method and Description |
---|---|
abstract Model |
Model.clone()
Clone the model.
|
Model |
Tile.getModel() |
Modifier and Type | Method and Description |
---|---|
void |
PointMatch.apply(Model model)
Apply a
Model to PointMatch.p1 , update distance. |
void |
Point.apply(Model model)
|
void |
Point.apply(Model model,
float amount)
|
void |
PointMatch.applyByStrength(Model model,
float amount)
Apply a
Model to PointMatch.p1 with a given amount, update
distance. |
boolean |
Model.betterThan(Model m)
less than operater to make the models comparable, returns false for error < 0
|
static boolean |
Model.test(Model model,
Collection<PointMatch> candidates,
Collection<PointMatch> inliers,
double epsilon,
double min_inlier_ratio)
Test the
Model for a set of point correspondence candidates. |
Constructor and Description |
---|
Tile(double width,
double height,
Model model)
Constructor
|
Tile(float width,
float height,
Model model)
Constructor
|
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