boofcv.factory.geo

Class FactoryMultiViewRobust

java.lang.Object

boofcv.factory.geo.FactoryMultiViewRobust

public class FactoryMultiViewRobust
extends java.lang.Object

Factory for creating robust false-positive tolerant estimation algorithms in multi-view geometry. These algorithms tend to have a lot of boilerplate associated with them and the goal of this factory is to make their use much easier and less error prone.

Constructor Summary

Constructors

Constructor and Description
FactoryMultiViewRobust()

Method Summary

Modifier and Type	Method and Description
static org.ddogleg.fitting.modelset.lmeds.LeastMedianOfSquares<georegression.struct.se.Se3_F64,AssociatedPair>	essentialLMedS(ConfigEssential essential, ConfigLMedS lmeds) Robust solution for estimating Se3_F64 using epipolar geometry from two views with LMedS.
static org.ddogleg.fitting.modelset.ransac.Ransac<georegression.struct.se.Se3_F64,AssociatedPair>	essentialRansac(ConfigEssential essential, ConfigRansac ransac) Robust solution for estimating Se3_F64 using epipolar geometry from two views with Ransac.
static org.ddogleg.fitting.modelset.lmeds.LeastMedianOfSquares<georegression.struct.homography.Homography2D_F64,AssociatedPair>	homographyLMedS(ConfigHomography homography, ConfigLMedS lmeds) Robust solution for estimating Homography2D_F64 with LMedS.
static org.ddogleg.fitting.modelset.ransac.Ransac<georegression.struct.homography.Homography2D_F64,AssociatedPair>	homographyRansac(ConfigHomography homography, ConfigRansac ransac) Robust solution for estimating Homography2D_F64 with Ransac.
static org.ddogleg.fitting.modelset.lmeds.LeastMedianOfSquares<georegression.struct.se.Se3_F64,Point2D3D>	pnpLMedS(ConfigPnP pnp, ConfigLMedS lmeds) Robust solution to PnP problem using LMedS.
static org.ddogleg.fitting.modelset.ransac.Ransac<georegression.struct.se.Se3_F64,Point2D3D>	pnpRansac(ConfigPnP pnp, ConfigRansac ransac) Robust solution to PnP problem using Ransac.

Methods inherited from class java.lang.Object

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

Constructor Detail

FactoryMultiViewRobust

public FactoryMultiViewRobust()

Method Detail

pnpLMedS

public static org.ddogleg.fitting.modelset.lmeds.LeastMedianOfSquares<georegression.struct.se.Se3_F64,Point2D3D> pnpLMedS(ConfigPnP pnp,
                                                                                                                          ConfigLMedS lmeds)

Robust solution to PnP problem using LMedS. Input observations are in normalized image coordinates.

• Error units is pixels squared.

See code for all the details.

Parameters:

pnp - PnP parameters. Can't be null.

lmeds - Parameters for LMedS. Can't be null.

Returns:

Robust Se3_F64 estimator

pnpRansac

public static org.ddogleg.fitting.modelset.ransac.Ransac<georegression.struct.se.Se3_F64,Point2D3D> pnpRansac(ConfigPnP pnp,
                                                                                                              ConfigRansac ransac)

Robust solution to PnP problem using Ransac. Input observations are in normalized image coordinates.

See code for all the details.

Parameters:

pnp - PnP parameters. Can't be null.

ransac - Parameters for RANSAC. Can't be null.

Returns:

Robust Se3_F64 estimator

essentialLMedS

public static org.ddogleg.fitting.modelset.lmeds.LeastMedianOfSquares<georegression.struct.se.Se3_F64,AssociatedPair> essentialLMedS(ConfigEssential essential,
                                                                                                                                     ConfigLMedS lmeds)

Robust solution for estimating Se3_F64 using epipolar geometry from two views with LMedS. Input observations are in normalized image coordinates.

• Error units is pixels squared times two

See code for all the details.

Parameters:

essential - Essential matrix estimation parameters. Can't be null.

lmeds - Parameters for RANSAC. Can't be null.

Returns:

Robust Se3_F64 estimator

essentialRansac

public static org.ddogleg.fitting.modelset.ransac.Ransac<georegression.struct.se.Se3_F64,AssociatedPair> essentialRansac(ConfigEssential essential,
                                                                                                                         ConfigRansac ransac)

Robust solution for estimating Se3_F64 using epipolar geometry from two views with Ransac. Input observations are in normalized image coordinates.

See code for all the details.

Parameters:

essential - Essential matrix estimation parameters. Can't be null.

ransac - Parameters for RANSAC. Can't be null.

Returns:

Robust Se3_F64 estimator

homographyLMedS

public static org.ddogleg.fitting.modelset.lmeds.LeastMedianOfSquares<georegression.struct.homography.Homography2D_F64,AssociatedPair> homographyLMedS(ConfigHomography homography,
                                                                                                                                                       ConfigLMedS lmeds)

Robust solution for estimating Homography2D_F64 with LMedS. Input observations are in pixel coordinates.

• Four point linear is used internally

• inlierThreshold is in pixels

See code for all the details.

Parameters:

homography - Homography estimation parameters. If null default is used.

lmeds - Parameters for LMedS. Can't be null.

Returns:

Homography estimator

homographyRansac

public static org.ddogleg.fitting.modelset.ransac.Ransac<georegression.struct.homography.Homography2D_F64,AssociatedPair> homographyRansac(ConfigHomography homography,
                                                                                                                                           ConfigRansac ransac)

Robust solution for estimating Homography2D_F64 with Ransac. Input observations are in pixel coordinates.

• Four point linear is used internally

• inlierThreshold is in pixels

See code for all the details.

Parameters:

homography - Homography estimation parameters. If null default is used.

ransac - Parameters for RANSAC. Can't be null.

Returns:

Homography estimator