- java.lang.Object
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- boofcv.examples.features.ExampleAssociatePoints<T,TD>
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public class ExampleAssociatePoints<T extends ImageGray,TD extends TupleDesc> extends java.lang.ObjectAfter interest points have been detected in two images the next step is to associate the two sets of images so that the relationship can be found. This is done by computing descriptors for each detected feature and associating them together. In the code below abstracted interfaces are used to allow different algorithms to be easily used. The cost of this abstraction is that detector/descriptor specific information is thrown away, potentially slowing down or degrading performance.
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Field Summary
Fields Modifier and Type Field and Description java.util.List<Point2D_F64>pointsAjava.util.List<Point2D_F64>pointsB
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Constructor Summary
Constructors Constructor and Description ExampleAssociatePoints(DetectDescribePoint<T,TD> detDesc, AssociateDescription<TD> associate, java.lang.Class<T> imageType)
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Method Summary
All Methods Static Methods Instance Methods Concrete Methods Modifier and Type Method and Description voidassociate(java.awt.image.BufferedImage imageA, java.awt.image.BufferedImage imageB)Detect and associate point features in the two images.static voidmain(java.lang.String[] args)
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Field Detail
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pointsA
public java.util.List<Point2D_F64> pointsA
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pointsB
public java.util.List<Point2D_F64> pointsB
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Constructor Detail
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ExampleAssociatePoints
public ExampleAssociatePoints(DetectDescribePoint<T,TD> detDesc, AssociateDescription<TD> associate, java.lang.Class<T> imageType)
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