| Package | Description |
|---|---|
| stitching.model |
| Modifier and Type | Method and Description |
|---|---|
static ArrayList<PointMatch> |
PointMatch.flip(Collection<PointMatch> matches)
Flip symmetrically, weights remains unchanged.
|
ArrayList<PointMatch> |
Tile.getMatches() |
| Modifier and Type | Method and Description |
|---|---|
boolean |
Tile.addMatch(PointMatch match)
Add one match.
|
| Modifier and Type | Method and Description |
|---|---|
boolean |
Tile.addMatches(Collection<PointMatch> more)
Add more
PointMatches. |
void |
Tile.connect(Tile o,
Collection<PointMatch> matches)
connect two tiles by a set of point correspondences
re-weighs the point correpondences
We set a weigh of 1.0 / num_matches to each correspondence to equalize
the connections between tiles during minimization.
|
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.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.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.
|
void |
TranslationModel3D.fit(Collection<PointMatch> matches) |
void |
TranslationModel2D.fit(Collection<PointMatch> matches) |
abstract void |
Model.fit(Collection<PointMatch> matches)
Fit the
Model to a set of data points minimizing the global
transfer error. |
static ArrayList<PointMatch> |
PointMatch.flip(Collection<PointMatch> matches)
Flip symmetrically, weights remains unchanged.
|
static <M extends Model> |
Model.ransac(Class<M> modelClass,
List<PointMatch> candidates,
Collection<PointMatch> inliers,
int iterations,
double epsilon,
double min_inlier_ratio)
|
static <M extends Model> |
Model.ransac(Class<M> modelClass,
List<PointMatch> candidates,
Collection<PointMatch> inliers,
int iterations,
double epsilon,
double min_inlier_ratio)
|
void |
TranslationModel3D.shake(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 |
TranslationModel2D.shake(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(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
|
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. |
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. |
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