Example PnP - Revision history

Peter at 19:49, 12 July 2021

2021-07-12T19:49:59Z

Peter at 02:43, 22 December 2020

2020-12-22T02:43:04Z

← Older revision		Revision as of 02:43, 22 December 2020
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	Example Code:		Example Code:
	* [https://github.com/lessthanoptimal/BoofCV/blob/v0.33/examples/src/main/java/boofcv/examples/sfm/ExamplePnP.java ExamplePnP.java]		* [https://github.com/lessthanoptimal/BoofCV/blob/v0.37/examples/src/main/java/boofcv/examples/sfm/ExamplePnP.java ExamplePnP.java]

	Concepts:		Concepts:
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	// create an arbitrary transform from world to camera reference frames		// create an arbitrary transform from world to camera reference frames
	Se3_F64 worldToCamera = new Se3_F64();		Se3_F64 worldToCamera = new Se3_F64();
	worldToCamera.getT().~~set~~(5, 10, -7);		worldToCamera.getT().setTo(5, 10, -7);
	ConvertRotation3D_F64.eulerToMatrix(EulerType.XYZ,0.1,-0.3,0,worldToCamera.getR());		ConvertRotation3D_F64.eulerToMatrix(EulerType.XYZ,0.1,-0.3,0,worldToCamera.getR());

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	// Save the perfect noise free observation		// Save the perfect noise free observation
	Point2D3D o = new Point2D3D();		Point2D3D o = new Point2D3D();
	o.getLocation().~~set~~(worldPt);		o.getLocation().setTo(worldPt);
	o.getObservation().~~set~~(norm.x,norm.y);		o.getObservation().setTo(norm.x,norm.y);

	observations.add(o);		observations.add(o);
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	Point2D3D o = new Point2D3D();		Point2D3D o = new Point2D3D();
	o.observation.~~set~~(p.observation);		o.observation.setTo(p.observation);
	o.location.x = p.location.x + rand.nextGaussian()*5;		o.location.x = p.location.x + rand.nextGaussian()*5;
	o.location.y = p.location.y + rand.nextGaussian()*5;		o.location.y = p.location.y + rand.nextGaussian()*5;

Peter at 15:00, 15 March 2019

2019-03-15T15:00:34Z

← Older revision		Revision as of 15:00, 15 March 2019
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	Example Code:		Example Code:
	* [https://github.com/lessthanoptimal/BoofCV/blob/v0.32/examples/src/main/java/boofcv/examples/sfm/ExamplePnP.java ExamplePnP.java]		* [https://github.com/lessthanoptimal/BoofCV/blob/v0.33/examples/src/main/java/boofcv/examples/sfm/ExamplePnP.java ExamplePnP.java]

	Concepts:		Concepts:
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	// describes the intrinsic camera parameters.		// describes the intrinsic camera parameters.
	~~CameraPinholeRadial~~ intrinsic = new ~~CameraPinholeRadial~~(500,490,0,320,240,640,480).fsetRadial(0.1,-0.05);		CameraPinholeBrown intrinsic = new CameraPinholeBrown(500,490,0,320,240,640,480).fsetRadial(0.1,-0.05);

	// Used to generate random observations		// Used to generate random observations

Peter at 04:02, 27 December 2018

2018-12-27T04:02:52Z

← Older revision		Revision as of 04:02, 27 December 2018
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	Example Code:		Example Code:
	* [https://github.com/lessthanoptimal/BoofCV/blob/v0.31/examples/src/main/java/boofcv/examples/sfm/ExamplePnP.java ExamplePnP.java]		* [https://github.com/lessthanoptimal/BoofCV/blob/v0.32/examples/src/main/java/boofcv/examples/sfm/ExamplePnP.java ExamplePnP.java]

	Concepts:		Concepts:
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	// We can no longer trust that each point is a real observation. Let's use RANSAC to separate the points		// We can no longer trust that each point is a real observation. Let's use RANSAC to separate the points
	// You will need to tune the number of iterations and inlier threshold!!!		// You will need to tune the number of iterations and inlier threshold!!!
	~~RansacMultiView~~<Se3_F64,Point2D3D> ransac =		ModelMatcherMultiview<Se3_F64,Point2D3D> ransac =
	FactoryMultiViewRobust.pnpRansac(new ConfigPnP(),new ConfigRansac(300,1.0));		FactoryMultiViewRobust.pnpRansac(new ConfigPnP(),new ConfigRansac(300,1.0));
	ransac.setIntrinsic(0,intrinsic);		ransac.setIntrinsic(0,intrinsic);
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	// transform from pixel coordinates to normalized pixel coordinates, which removes lens distortion		// transform from pixel coordinates to normalized pixel coordinates, which removes lens distortion
	Point2Transform2_F64 pixelToNorm = ~~LensDistortionOps~~.narrow(intrinsic).undistort_F64(true,false);		Point2Transform2_F64 pixelToNorm = LensDistortionFactory.narrow(intrinsic).undistort_F64(true,false);

	List<Point2D3D> observations = new ArrayList<>();		List<Point2D3D> observations = new ArrayList<>();

Peter at 03:03, 17 October 2018

2018-10-17T03:03:25Z

← Older revision		Revision as of 03:03, 17 October 2018
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	Example Code:		Example Code:
	* [https://github.com/lessthanoptimal/BoofCV/blob/v0.27/examples/src/boofcv/examples/sfm/ExamplePnP.java ExamplePnP.java]		* [https://github.com/lessthanoptimal/BoofCV/blob/v0.31/examples/src/main/java/boofcv/examples/sfm/ExamplePnP.java ExamplePnP.java]

	Concepts:		Concepts:
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	// 10 iterations is what JavaDoc recommends, but might need to be tuned.		// 10 iterations is what JavaDoc recommends, but might need to be tuned.
	// 0 test points. This parameters is actually ignored because EPNP only returns a single solution		// 0 test points. This parameters is actually ignored because EPNP only returns a single solution
	Estimate1ofPnP pnp = FactoryMultiView.~~computePnP_1~~(EnumPNP.EPNP, 10, 0);		Estimate1ofPnP pnp = FactoryMultiView.pnp_1(EnumPNP.EPNP, 10, 0);

	Se3_F64 worldToCamera = new Se3_F64();		Se3_F64 worldToCamera = new Se3_F64();
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	// For some applications the EPNP solution might be good enough, but let's refine it		// For some applications the EPNP solution might be good enough, but let's refine it
	RefinePnP refine = FactoryMultiView.~~refinePnP~~(1e-8,200);		RefinePnP refine = FactoryMultiView.pnpRefine(1e-8,200);

	Se3_F64 refinedWorldToCamera = new Se3_F64();		Se3_F64 refinedWorldToCamera = new Se3_F64();
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	// We can no longer trust that each point is a real observation. Let's use RANSAC to separate the points		// We can no longer trust that each point is a real observation. Let's use RANSAC to separate the points
	// You will need to tune the number of iterations and inlier threshold!!!		// You will need to tune the number of iterations and inlier threshold!!!
	~~Ransac~~<Se3_F64,Point2D3D> ransac =		RansacMultiView<Se3_F64,Point2D3D> ransac =
	FactoryMultiViewRobust.pnpRansac(new ConfigPnP(~~intrinsic~~),new ConfigRansac(300,1.0));		FactoryMultiViewRobust.pnpRansac(new ConfigPnP(),new ConfigRansac(300,1.0));
			ransac.setIntrinsic(0,intrinsic);

	// Observations must be in normalized image coordinates! See javadoc of pnpRansac		// Observations must be in normalized image coordinates! See javadoc of pnpRansac
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	// You will most likely want to refine this solution too. Can make a difference with real world data		// You will most likely want to refine this solution too. Can make a difference with real world data
	RefinePnP refine = FactoryMultiView.~~refinePnP~~(1e-8,200);		RefinePnP refine = FactoryMultiView.pnpRefine(1e-8,200);

	Se3_F64 refinedWorldToCamera = new Se3_F64();		Se3_F64 refinedWorldToCamera = new Se3_F64();
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	double y = rand.nextDouble()*intrinsic.height;		double y = rand.nextDouble()*intrinsic.height;

			// Convert to normalized image coordinates because that's what PNP needs.
			// it can't process pixel coordinates
	pixelToNorm.compute(x,y,norm);		pixelToNorm.compute(x,y,norm);

Peter at 16:08, 17 August 2017

2017-08-17T16:08:23Z

← Older revision		Revision as of 16:08, 17 August 2017
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	Example Code:		Example Code:
	* [https://github.com/lessthanoptimal/BoofCV/blob/v0.25/examples/src/boofcv/examples/sfm/ExamplePnP.java ExamplePnP.java]		* [https://github.com/lessthanoptimal/BoofCV/blob/v0.27/examples/src/boofcv/examples/sfm/ExamplePnP.java ExamplePnP.java]

	Concepts:		Concepts:

Peter at 16:08, 17 August 2017

2017-08-17T16:08:14Z

← Older revision		Revision as of 16:08, 17 August 2017
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	FactoryMultiViewRobust.pnpRansac(new ConfigPnP(intrinsic),new ConfigRansac(300,1.0));		FactoryMultiViewRobust.pnpRansac(new ConfigPnP(intrinsic),new ConfigRansac(300,1.0));

			// Observations must be in normalized image coordinates! See javadoc of pnpRansac
	if( !ransac.process(observations) )		if( !ransac.process(observations) )
	throw new RuntimeException("Probably got bad input data with NaN inside of it");		throw new RuntimeException("Probably got bad input data with NaN inside of it");
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	/**		/**
	* Generates synthetic observations randomly in front of the camera		* Generates synthetic observations randomly in front of the camera. Observations are in normalized image
			* coordinates and not pixels! See {@link PerspectiveOps#convertPixelToNorm} for how to go from pixels
			* to normalized image coordinates.
	*/		*/
	public List<Point2D3D> createObservations( Se3_F64 worldToCamera , int total ) {		public List<Point2D3D> createObservations( Se3_F64 worldToCamera , int total ) {
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	// transform from pixel coordinates to normalized pixel coordinates, which removes lens distortion		// transform from pixel coordinates to normalized pixel coordinates, which removes lens distortion
	Point2Transform2_F64 pixelToNorm = LensDistortionOps.~~transformPoint~~(intrinsic).undistort_F64(true,false);		Point2Transform2_F64 pixelToNorm = LensDistortionOps.narrow(intrinsic).undistort_F64(true,false);

	List<Point2D3D> observations = new ArrayList<>();		List<Point2D3D> observations = new ArrayList<>();

Peter at 00:54, 2 December 2016

2016-12-02T00:54:59Z

← Older revision		Revision as of 00:54, 2 December 2016
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	Example Code:		Example Code:
	* [https://github.com/lessthanoptimal/BoofCV/blob/v0.21/examples/src/boofcv/examples/sfm/ExamplePnP.java ExamplePnP.java]		* [https://github.com/lessthanoptimal/BoofCV/blob/v0.25/examples/src/boofcv/examples/sfm/ExamplePnP.java ExamplePnP.java]

	Concepts:		Concepts:
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	// describes the intrinsic camera parameters.		// describes the intrinsic camera parameters.
	~~IntrinsicParameters~~ intrinsic = new ~~IntrinsicParameters~~(500,490,0,320,240,640,480).fsetRadial(0.1,-0.05);		CameraPinholeRadial intrinsic = new CameraPinholeRadial(500,490,0,320,240,640,480).fsetRadial(0.1,-0.05);

	// Used to generate random observations		// Used to generate random observations
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	// transform from pixel coordinates to normalized pixel coordinates, which removes lens distortion		// transform from pixel coordinates to normalized pixel coordinates, which removes lens distortion
	~~PointTransform_F64~~ pixelToNorm = LensDistortionOps.transformPoint(intrinsic).undistort_F64(true,false);		Point2Transform2_F64 pixelToNorm = LensDistortionOps.transformPoint(intrinsic).undistort_F64(true,false);

	List<Point2D3D> observations = new ArrayList<~~Point2D3D~~>();		List<Point2D3D> observations = new ArrayList<>();

	Point2D_F64 norm = new Point2D_F64();		Point2D_F64 norm = new Point2D_F64();

Peter at 05:18, 24 January 2016

2016-01-24T05:18:22Z

← Older revision		Revision as of 05:18, 24 January 2016
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	Example Code:		Example Code:
	* [https://github.com/lessthanoptimal/BoofCV/blob/v0.18/examples/src/boofcv/examples/sfm/ExamplePnP.java ExamplePnP.java]		* [https://github.com/lessthanoptimal/BoofCV/blob/v0.21/examples/src/boofcv/examples/sfm/ExamplePnP.java ExamplePnP.java]

	Concepts:		Concepts:
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	Se3_F64 worldToCamera = new Se3_F64();		Se3_F64 worldToCamera = new Se3_F64();
	worldToCamera.getT().set(5, 10, -7);		worldToCamera.getT().set(5, 10, -7);
	~~RotationMatrixGenerator~~.~~eulerXYZ~~(0.1,-0.3,0,worldToCamera.getR());		ConvertRotation3D_F64.eulerToMatrix(EulerType.XYZ,0.1,-0.3,0,worldToCamera.getR());

	ExamplePnP app = new ExamplePnP();		ExamplePnP app = new ExamplePnP();

Peter at 02:12, 20 September 2015

2015-09-20T02:12:30Z

← Older revision		Revision as of 02:12, 20 September 2015
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	/**		/**
	* Generates synthetic ~~observatiosn~~ randomly in front of the camera		* Generates synthetic observations randomly in front of the camera
	*/		*/
	public List<Point2D3D> createObservations( Se3_F64 worldToCamera , int total ) {		public List<Point2D3D> createObservations( Se3_F64 worldToCamera , int total ) {

← Older revision		Revision as of 19:49, 12 July 2021
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	Example Code:		Example Code:
	* [https://github.com/lessthanoptimal/BoofCV/blob/v0.37/examples/src/main/java/boofcv/examples/sfm/ExamplePnP.java ExamplePnP.java]		* [https://github.com/lessthanoptimal/BoofCV/blob/v0.38/examples/src/main/java/boofcv/examples/sfm/ExamplePnP.java ExamplePnP.java]

	Concepts:		Concepts:
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	/**		/**
	* The Perspective-n-Point problem or PnP for short, is a problem where there are N observations of points with		* The Perspective-n-Point problem or PnP for short, is a problem where there are N observations of points with
	* known 3D coordinates. The output is the pose of the camera observing the points. The minimal solution requires		* known 3D coordinates. The output is the pose of the camera observing the points. The minimal solution requires
	* 3-points but produces multiple solutions. BoofCV provide several solutions to the PnP problem and the example		* 3-points but produces multiple solutions. BoofCV provide several solutions to the PnP problem and the example
	* below demonstrates how to use them.		* below demonstrates how to use them.
	*		*
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	// Compute a single solution using EPNP		// Compute a single solution using EPNP
	// 10 iterations is what JavaDoc recommends, but might need to be tuned.		// 10 iterations is what JavaDoc recommends, but might need to be tuned.
	// 0 test points. This parameters is actually ignored because EPNP only returns a single solution		// 0 test points. This parameters is actually ignored because EPNP only returns a single solution
	Estimate1ofPnP pnp = FactoryMultiView.pnp_1(EnumPNP.EPNP, 10, 0);		Estimate1ofPnP pnp = FactoryMultiView.pnp_1(EnumPNP.EPNP, 10, 0);

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	*/		*/
	public Se3_F64 estimateOutliers( List<Point2D3D> observations ) {		public Se3_F64 estimateOutliers( List<Point2D3D> observations ) {
	// We can no longer trust that each point is a real observation. Let's use RANSAC to separate the points		// We can no longer trust that each point is a real observation. Let's use RANSAC to separate the points
	// You will need to tune the number of iterations and inlier threshold!!!		// You will need to tune the number of iterations and inlier threshold!!!
	ModelMatcherMultiview<Se3_F64,Point2D3D> ransac =		ModelMatcherMultiview<Se3_F64,Point2D3D> ransac =
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	Se3_F64 worldToCamera = ransac.getModelParameters();		Se3_F64 worldToCamera = ransac.getModelParameters();

	// You will most likely want to refine this solution too. Can make a difference with real world data		// You will most likely want to refine this solution too. Can make a difference with real world data
	RefinePnP refine = FactoryMultiView.pnpRefine(1e-8,200);		RefinePnP refine = FactoryMultiView.pnpRefine(1e-8,200);

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	/**		/**
	* Generates synthetic observations randomly in front of the camera. Observations are in normalized image		* Generates synthetic observations randomly in front of the camera. Observations are in normalized image
	* coordinates and not pixels! See {@link PerspectiveOps#convertPixelToNorm} for how to go from pixels		* coordinates and not pixels! See {@link PerspectiveOps#convertPixelToNorm} for how to go from pixels
	* to normalized image coordinates.		* to normalized image coordinates.