Package boofcv.alg.feature.associate

Class AssociateGreedyBruteForce2D_MT<D>

java.lang.Object

boofcv.alg.feature.associate.AssociateGreedyBase<D>

boofcv.alg.feature.associate.AssociateGreedyBase2D<D>

boofcv.alg.feature.associate.AssociateGreedyBruteForce2D_MT<D>

@Generated("boofcv.alg.feature.associate.AssociateGreedyBruteForce2D")
public class AssociateGreedyBruteForce2D_MT<D>
extends AssociateGreedyBase2D<D>

Greedily assigns two features to each other based on their scores while pruning features based on their distance apart. it is a brute force algorithm since the distance between all possible pairs of source and destination and checked to see if they are too far apart. Distance is computed using the provided distance function. Examples of distance include Euclidean and Epipolar.

Field Summary

Fields inherited from class boofcv.alg.feature.associate.AssociateGreedyBase2D

descDst, descSrc, distanceFunction, distances, locationDst, locationSrc, maxDistanceLength, maxDistanceUnits

Constructor Summary

Constructors

Constructor	Description
AssociateGreedyBruteForce2D_MT(ScoreAssociation<D> scoreAssociation, AssociateImageDistanceFunction distanceFunction)	Specifies score mechanism

Method Summary

Modifier and Type	Method	Description
void	associate()	Performs association by computing a 2D score matrix.

Methods inherited from class boofcv.alg.feature.associate.AssociateGreedyBase2D

init, setDestination, setSource

Methods inherited from class boofcv.alg.feature.associate.AssociateGreedyBase

forwardsBackwards, setMaxFitError, setupForAssociate

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Details

AssociateGreedyBruteForce2D_MT

public AssociateGreedyBruteForce2D_MT(ScoreAssociation<D> scoreAssociation,
 AssociateImageDistanceFunction distanceFunction)

Specifies score mechanism

Parameters:

scoreAssociation - How features are scored.

Method Details

associate

public void associate()

Performs association by computing a 2D score matrix. First the score matrix is computed while finding the best fit relative to the source. Then additional sanity checks are done to see if it's a valid match/

Specified by:

associate in class AssociateGreedyBase2D<D>