Example Associate Interest Points - Revision history

Peter at 20:30, 17 January 2022

2022-01-17T20:30:09Z

← Older revision		Revision as of 20:30, 17 January 2022
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	Example Code:		Example Code:
	* [https://github.com/lessthanoptimal/BoofCV/tree/v0.38/examples/src/main/java/boofcv/examples/features/ExampleAssociatePoints.java ExampleAssociatePoints.java]		* [https://github.com/lessthanoptimal/BoofCV/tree/v0.40/examples/src/main/java/boofcv/examples/features/ExampleAssociatePoints.java ExampleAssociatePoints.java]

	Concepts:		Concepts:
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	Class<T> imageType;		Class<T> imageType;

	public ExampleAssociatePoints(DetectDescribePoint<T, TD> detDesc,		public ExampleAssociatePoints( DetectDescribePoint<T, TD> detDesc,
	AssociateDescription<TD> associate,		AssociateDescription<TD> associate,
	Class<T> imageType) {		Class<T> imageType ) {
	this.detDesc = detDesc;		this.detDesc = detDesc;
	this.associate = associate;		this.associate = associate;
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	* Detect and associate point features in the two images. Display the results.		* Detect and associate point features in the two images. Display the results.
	*/		*/
	public void associate( BufferedImage imageA , BufferedImage imageB )		public void associate( BufferedImage imageA, BufferedImage imageB ) {
	{
	T inputA = ConvertBufferedImage.convertFromSingle(imageA, null, imageType);		T inputA = ConvertBufferedImage.convertFromSingle(imageA, null, imageType);
	T inputB = ConvertBufferedImage.convertFromSingle(imageB, null, imageType);		T inputB = ConvertBufferedImage.convertFromSingle(imageB, null, imageType);
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	// stores the description of detected interest points		// stores the description of detected interest points
	DogArray<TD> descA = UtilFeature.createArray(detDesc,100);		DogArray<TD> descA = UtilFeature.createArray(detDesc, 100);
	DogArray<TD> descB = UtilFeature.createArray(detDesc,100);		DogArray<TD> descB = UtilFeature.createArray(detDesc, 100);

	// describe each image using interest points		// describe each image using interest points
	describeImage(inputA,pointsA,descA);		describeImage(inputA, pointsA, descA);
	describeImage(inputB,pointsB,descB);		describeImage(inputB, pointsB, descB);

	// Associate features between the two images		// Associate features between the two images
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	// display the results		// display the results
	AssociationPanel panel = new AssociationPanel(20);		AssociationPanel panel = new AssociationPanel(20);
	panel.setAssociation(pointsA,pointsB,associate.getMatches());		panel.setAssociation(pointsA, pointsB, associate.getMatches());
	panel.setImages(imageA,imageB);		panel.setImages(imageA, imageB);

	ShowImages.showWindow(panel,"Associated Features",true);		ShowImages.showWindow(panel, "Associated Features", true);
	}		}

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	* Detects features inside the two images and computes descriptions at those points.		* Detects features inside the two images and computes descriptions at those points.
	*/		*/
	private void describeImage(T input, List<Point2D_F64> points, DogArray<TD> descs )		private void describeImage( T input, List<Point2D_F64> points, DogArray<TD> descs ) {
	{
	detDesc.detect(input);		detDesc.detect(input);

	for( int i = 0; i < detDesc.getNumberOfFeatures(); i++ ) {		for (int i = 0; i < detDesc.getNumberOfFeatures(); i++) {
	points.add( detDesc.getLocation(i).copy() );		points.add(detDesc.getLocation(i).copy());
	descs.grow().setTo(detDesc.getDescription(i));		descs.grow().setTo(detDesc.getDescription(i));
	}		}
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	// select which algorithms to use		// select which algorithms to use
	DetectDescribePoint detDesc = FactoryDetectDescribe.		DetectDescribePoint detDesc = FactoryDetectDescribe.
	surfStable(new ConfigFastHessian(1, 2, 300, 1, 9, 4, 4), null,null, imageType);		surfStable(new ConfigFastHessian(1, 2, 300, 1, 9, 4, 4), null, null, imageType);
	// sift(new ConfigCompleteSift(0,5,600));		// sift(new ConfigCompleteSift(0,5,600));

	ScoreAssociation scorer = FactoryAssociation.defaultScore(detDesc.getDescriptionType());		ScoreAssociation scorer = FactoryAssociation.defaultScore(detDesc.getDescriptionType());
	AssociateDescription associate = FactoryAssociation.greedy(new ConfigAssociateGreedy(true),scorer);		AssociateDescription associate = FactoryAssociation.greedy(new ConfigAssociateGreedy(true), scorer);

	// load and match images		// load and match images
	ExampleAssociatePoints app = new ExampleAssociatePoints(detDesc,associate,imageType);		ExampleAssociatePoints app = new ExampleAssociatePoints(detDesc, associate, imageType);

	BufferedImage imageA = UtilImageIO.~~loadImage~~(UtilIO.pathExample("stitch/kayak_01.jpg"));		BufferedImage imageA = UtilImageIO.loadImageNotNull(UtilIO.pathExample("stitch/kayak_01.jpg"));
	BufferedImage imageB = UtilImageIO.~~loadImage~~(UtilIO.pathExample("stitch/kayak_03.jpg"));		BufferedImage imageB = UtilImageIO.loadImageNotNull(UtilIO.pathExample("stitch/kayak_03.jpg"));

	app.associate(imageA,imageB);		app.associate(imageA, imageB);
	}		}
	}		}
	</syntaxhighlight>		</syntaxhighlight>

Peter at 17:21, 12 July 2021

2021-07-12T17:21:28Z

← Older revision		Revision as of 17:21, 12 July 2021
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	Example Code:		Example Code:
	* [https://github.com/lessthanoptimal/BoofCV/tree/v0.37/examples/src/main/java/boofcv/examples/features/ExampleAssociatePoints.java ExampleAssociatePoints.java]		* [https://github.com/lessthanoptimal/BoofCV/tree/v0.38/examples/src/main/java/boofcv/examples/features/ExampleAssociatePoints.java ExampleAssociatePoints.java]

	Concepts:		Concepts:
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	/**		/**
	* After interest points have been detected in two images the next step is to associate the two		* After 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		* 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		* 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		* 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.		* specific information is thrown away, potentially slowing down or degrading performance.
	*		*
	* @author Peter Abeles		* @author Peter Abeles
	*/		*/
	public class ExampleAssociatePoints<T extends ImageGray<T>, TD extends TupleDesc> {		public class ExampleAssociatePoints<T extends ImageGray<T>, TD extends TupleDesc<TD>> {

	// algorithm used to detect and describe interest points		// algorithm used to detect and describe interest points
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	/**		/**
	* Detect and associate point features in the two images. Display the results.		* Detect and associate point features in the two images. Display the results.
	*/		*/
	public void associate( BufferedImage imageA , BufferedImage imageB )		public void associate( BufferedImage imageA , BufferedImage imageB )
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	// stores the description of detected interest points		// stores the description of detected interest points
	DogArray<TD> descA = UtilFeature.~~createQueue~~(detDesc,100);		DogArray<TD> descA = UtilFeature.createArray(detDesc,100);
	DogArray<TD> descB = UtilFeature.~~createQueue~~(detDesc,100);		DogArray<TD> descB = UtilFeature.createArray(detDesc,100);

	// describe each image using interest points		// describe each image using interest points

Peter at 19:56, 21 December 2020

2020-12-21T19:56:09Z

← Older revision		Revision as of 19:56, 21 December 2020
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	Example Code:		Example Code:
	* [https://github.com/lessthanoptimal/BoofCV/tree/v0.36/examples/src/main/java/boofcv/examples/features/ExampleAssociatePoints.java ExampleAssociatePoints.java]		* [https://github.com/lessthanoptimal/BoofCV/tree/v0.37/examples/src/main/java/boofcv/examples/features/ExampleAssociatePoints.java ExampleAssociatePoints.java]

	Concepts:		Concepts:
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	// stores the description of detected interest points		// stores the description of detected interest points
	~~FastQueue~~<TD> descA = UtilFeature.createQueue(detDesc,100);		DogArray<TD> descA = UtilFeature.createQueue(detDesc,100);
	~~FastQueue~~<TD> descB = UtilFeature.createQueue(detDesc,100);		DogArray<TD> descB = UtilFeature.createQueue(detDesc,100);

	// describe each image using interest points		// describe each image using interest points
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	* Detects features inside the two images and computes descriptions at those points.		* Detects features inside the two images and computes descriptions at those points.
	*/		*/
	private void describeImage(T input, List<Point2D_F64> points, ~~FastQueue~~<TD> descs )		private void describeImage(T input, List<Point2D_F64> points, DogArray<TD> descs )
	{		{
	detDesc.detect(input);		detDesc.detect(input);
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	}		}

	public static void main( String ~~args~~[] ) {		public static void main( String[] args ) {

	Class imageType = GrayF32.class;		Class imageType = GrayF32.class;

Peter at 05:06, 18 May 2020

2020-05-18T05:06:27Z

← Older revision		Revision as of 05:06, 18 May 2020
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	Example Code:		Example Code:
	* [https://github.com/lessthanoptimal/BoofCV/~~blob~~/v0.36/examples/src/boofcv/examples/features/ExampleAssociatePoints.java ExampleAssociatePoints.java]		* [https://github.com/lessthanoptimal/BoofCV/tree/v0.36/examples/src/main/java/boofcv/examples/features/ExampleAssociatePoints.java ExampleAssociatePoints.java]

	Concepts:		Concepts:

Peter at 05:01, 18 May 2020

2020-05-18T05:01:44Z

← Older revision		Revision as of 05:01, 18 May 2020
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	Example Code:		Example Code:
	* [https://github.com/lessthanoptimal/BoofCV/blob/v0.27/examples/src/boofcv/examples/features/ExampleAssociatePoints.java ExampleAssociatePoints.java]		* [https://github.com/lessthanoptimal/BoofCV/blob/v0.36/examples/src/boofcv/examples/features/ExampleAssociatePoints.java ExampleAssociatePoints.java]

	Concepts:		Concepts:
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	ScoreAssociation scorer = FactoryAssociation.defaultScore(detDesc.getDescriptionType());		ScoreAssociation scorer = FactoryAssociation.defaultScore(detDesc.getDescriptionType());
	AssociateDescription associate = FactoryAssociation.greedy(scorer~~, Double.MAX_VALUE, true~~);		AssociateDescription associate = FactoryAssociation.greedy(new ConfigAssociateGreedy(true),scorer);

	// load and match images		// load and match images

Peter at 15:31, 17 August 2017

2017-08-17T15:31:18Z

← Older revision		Revision as of 15:31, 17 August 2017
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	Example Code:		Example Code:
	* [https://github.com/lessthanoptimal/BoofCV/blob/v0.25/examples/src/boofcv/examples/features/ExampleAssociatePoints.java ExampleAssociatePoints.java]		* [https://github.com/lessthanoptimal/BoofCV/blob/v0.27/examples/src/boofcv/examples/features/ExampleAssociatePoints.java ExampleAssociatePoints.java]

	Concepts:		Concepts:
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	* @author Peter Abeles		* @author Peter Abeles
	*/		*/
	public class ExampleAssociatePoints<T extends ImageGray, TD extends TupleDesc> {		public class ExampleAssociatePoints<T extends ImageGray<T>, TD extends TupleDesc> {

	// algorithm used to detect and describe interest points		// algorithm used to detect and describe interest points

Peter at 22:31, 1 December 2016

2016-12-01T22:31:15Z

← Older revision		Revision as of 22:31, 1 December 2016
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	Example Code:		Example Code:
	* [https://github.com/lessthanoptimal/BoofCV/blob/v0.23/examples/src/boofcv/examples/features/ExampleAssociatePoints.java ExampleAssociatePoints.java]		* [https://github.com/lessthanoptimal/BoofCV/blob/v0.25/examples/src/boofcv/examples/features/ExampleAssociatePoints.java ExampleAssociatePoints.java]

	Concepts:		Concepts:
	* Describe point features		* Describe point features
	* Associate descriptions		* Associate descriptions

	~~Relevant Applets:~~
	* [[Applet_Description_Region\| Describe Points]]
	* [[Applet_Associate_Points\| Associate Points]]

	= Example Code =		= Example Code =
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	// stores the location of detected interest points		// stores the location of detected interest points
	pointsA = new ArrayList<~~Point2D_F64~~>();		pointsA = new ArrayList<>();
	pointsB = new ArrayList<~~Point2D_F64~~>();		pointsB = new ArrayList<>();

	// stores the description of detected interest points		// stores the description of detected interest points

Peter at 05:15, 28 March 2016

2016-03-28T05:15:07Z

← Older revision		Revision as of 05:15, 28 March 2016
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	Example Code:		Example Code:
	* [https://github.com/lessthanoptimal/BoofCV/blob/v0.21/examples/src/boofcv/examples/features/ExampleAssociatePoints.java ExampleAssociatePoints.java]		* [https://github.com/lessthanoptimal/BoofCV/blob/v0.23/examples/src/boofcv/examples/features/ExampleAssociatePoints.java ExampleAssociatePoints.java]

	Concepts:		Concepts:
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	* @author Peter Abeles		* @author Peter Abeles
	*/		*/
	public class ExampleAssociatePoints<T extends ~~ImageSingleBand~~, TD extends TupleDesc> {		public class ExampleAssociatePoints<T extends ImageGray, TD extends TupleDesc> {

	// algorithm used to detect and describe interest points		// algorithm used to detect and describe interest points
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	public static void main( String args[] ) {		public static void main( String args[] ) {

	Class imageType = ~~ImageFloat32~~.class;		Class imageType = GrayF32.class;
	// Class imageType = ~~ImageUInt8~~.class;		// Class imageType = GrayU8.class;

	// select which algorithms to use		// select which algorithms to use

Peter at 04:58, 24 January 2016

2016-01-24T04:58:38Z

← Older revision		Revision as of 04:58, 24 January 2016
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	Example Code:		Example Code:
	* [https://github.com/lessthanoptimal/BoofCV/blob/v0.20/examples/src/boofcv/examples/features/ExampleAssociatePoints.java ExampleAssociatePoints.java]		* [https://github.com/lessthanoptimal/BoofCV/blob/v0.21/examples/src/boofcv/examples/features/ExampleAssociatePoints.java ExampleAssociatePoints.java]

	Concepts:		Concepts:
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	Class imageType = ImageFloat32.class;		Class imageType = ImageFloat32.class;
			// Class imageType = ImageUInt8.class;

	// select which algorithms to use		// select which algorithms to use
	DetectDescribePoint detDesc = FactoryDetectDescribe.surfStable(		DetectDescribePoint detDesc = FactoryDetectDescribe.
	new ConfigFastHessian(1, 2, ~~200~~, 1, 9, 4, 4), null,null, imageType);		surfStable(new ConfigFastHessian(1, 2, 300, 1, 9, 4, 4), null,null, imageType);
			// sift(new ConfigCompleteSift(0,5,600));

	ScoreAssociation scorer = FactoryAssociation.defaultScore(detDesc.getDescriptionType());		ScoreAssociation scorer = FactoryAssociation.defaultScore(detDesc.getDescriptionType());

Peter at 16:31, 9 November 2015

2015-11-09T16:31:58Z

← Older revision		Revision as of 16:31, 9 November 2015
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	Example Code:		Example Code:
	* [https://github.com/lessthanoptimal/BoofCV/blob/v0.19/examples/src/boofcv/examples/features/ExampleAssociatePoints.java ExampleAssociatePoints.java]		* [https://github.com/lessthanoptimal/BoofCV/blob/v0.20/examples/src/boofcv/examples/features/ExampleAssociatePoints.java ExampleAssociatePoints.java]

	Concepts:		Concepts:
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	ExampleAssociatePoints app = new ExampleAssociatePoints(detDesc,associate,imageType);		ExampleAssociatePoints app = new ExampleAssociatePoints(detDesc,associate,imageType);

	BufferedImage imageA = UtilImageIO.loadImage("~~../data/evaluation/~~stitch/kayak_01.jpg");		BufferedImage imageA = UtilImageIO.loadImage(UtilIO.pathExample("stitch/kayak_01.jpg"));
	BufferedImage imageB = UtilImageIO.loadImage("~~../data/evaluation/~~stitch/kayak_03.jpg");		BufferedImage imageB = UtilImageIO.loadImage(UtilIO.pathExample("stitch/kayak_03.jpg"));

	app.associate(imageA,imageB);		app.associate(imageA,imageB);