case class MultiBodyShapePoseAndIntensityPGA[DDomain[D] <: DiscreteDomain[D]](gp: DiscreteLowRankGaussianProcess[_3D, [D]MultiBodyObjectWithIntensity[D, DDomain], ShapePoseAndIntensityVector[_3D]], logExpMapping: PoseExpLogMapping[DDomain])(implicit warperMultiBodyObjectWithIntensity: WarperMultiBodyObjectWithIntensity[DDomain], ultiBodyObjectWarper: DomainWarp[_3D, [D]MultiBodyObject[D, DDomain]], warperDomainWithPoseAndIntensity: WarperDomainWithPoseAndIntensity[DDomain], warperInnerDomain: DomainWarp[_3D, DDomain], rng: Random) extends Product with Serializable

A MultiBodyShapeAndPosePGA models shape and pose variations across given examples of multi body objects as deformation fields using DiscreteLowRankGaussianProcess. the MultiBodyShapePoseAndIntensityPGA while modelling shape deformation fields as StatisticalMeshModel, it uses PoseExpLogMapping to linearise pose deformation fields. MultiBodyShapePoseAndIntensityPGA warps the MultiBodyObjectWithIntensity with the shape and pose deformation fields to produce a new MultiBodyObjectWithIntensity.

See also

DiscreteLowRankGaussianProcess

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Instance Constructors

  1. new MultiBodyShapePoseAndIntensityPGA(gp: DiscreteLowRankGaussianProcess[_3D, [D]MultiBodyObjectWithIntensity[D, DDomain], ShapePoseAndIntensityVector[_3D]], logExpMapping: PoseExpLogMapping[DDomain])(implicit warperMultiBodyObjectWithIntensity: WarperMultiBodyObjectWithIntensity[DDomain], ultiBodyObjectWarper: DomainWarp[_3D, [D]MultiBodyObject[D, DDomain]], warperDomainWithPoseAndIntensity: WarperDomainWithPoseAndIntensity[DDomain], warperInnerDomain: DomainWarp[_3D, DDomain], rng: Random)

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##: Int
    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  4. def PoseAndPoseModel: MultiBodyShapeAndPosePGA[DDomain]
  5. final def asInstanceOf[T0]: T0
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    Any
  6. def clone(): AnyRef
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    protected[lang]
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    @throws(classOf[java.lang.CloneNotSupportedException]) @native()
  7. final def eq(arg0: AnyRef): Boolean
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  8. def finalize(): Unit
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    @throws(classOf[java.lang.Throwable])
  9. final def getClass(): Class[_ <: AnyRef]
    Definition Classes
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    @native()
  10. val gp: DiscreteLowRankGaussianProcess[_3D, [D]MultiBodyObjectWithIntensity[D, DDomain], ShapePoseAndIntensityVector[_3D]]
  11. def instance(coeffs: DenseVector[Double]): MultiBodyObjectWithIntensity[_3D, DDomain]

    returns a MultiBodyObjectWithIntensity that corresponds to a combination of the basis functions with the given coefficients coeffs.

    returns a MultiBodyObjectWithIntensity that corresponds to a combination of the basis functions with the given coefficients coeffs.

    See also

    DiscreteLowRankGaussianProcess.instance

  12. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  13. val logExpMapping: PoseExpLogMapping[DDomain]
  14. val mean: MultiBodyObjectWithIntensity[_3D, DDomain]

    The mean MultiBodyObjectWithIntensity

    The mean MultiBodyObjectWithIntensity

    See also

    DiscreteLowRankGaussianProcess.mean

  15. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  16. def newReference(newReference: MultiBodyObjectWithIntensity[_3D, DDomain], interpolator: FieldInterpolator[_3D, [D]MultiBodyObjectWithIntensity[D, DDomain], ShapePoseAndIntensityVector[_3D]], newLogExpMapping: PoseExpLogMapping[DDomain]): MultiBodyShapePoseAndIntensityPGA[DDomain]

    Warps the reference MultiBodyObjectWithIntensity to a new reference MultiBodyObjectWithIntensity.

    Warps the reference MultiBodyObjectWithIntensity to a new reference MultiBodyObjectWithIntensity. The space spanned by the model is not affected.

  17. final def notify(): Unit
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    @native()
  18. final def notifyAll(): Unit
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    @native()
  19. def posterior(trainingData: List[IndexedSeq[(PointId, Point[_3D], MultivariateNormalDistribution)]]): MultiBodyShapePoseAndIntensityPGA[DDomain]

    Similar to Point[_3D], Double)], but the training data is defined by specifying the target point instead of the displacement vector

  20. def posterior(trainingData: List[IndexedSeq[(PointId, Point[_3D])]], sigma2: Double): MultiBodyShapePoseAndIntensityPGA[DDomain]

    Similar to Point[_3D])], sigma2: Double), but the training data is defined by specifying the target point instead of the displacement vector

  21. def productElementNames: Iterator[String]
    Definition Classes
    Product
  22. def sample(): MultiBodyObjectWithIntensity[_3D, DDomain]

    draws a random MultiBodyObjectWithIntensity.

    draws a random MultiBodyObjectWithIntensity.

    See also

    DiscreteLowRankGaussianProcess.sample

  23. final def synchronized[T0](arg0: => T0): T0
    Definition Classes
    AnyRef
  24. def transform(rigidTransform: RigidTransformation[_3D]): MultiBodyShapePoseAndIntensityPGA[DDomain]

    transform the MultiBodyShapePoseAndIntensityPGA using the given rigid transform.

    transform the MultiBodyShapePoseAndIntensityPGA using the given rigid transform. The spanned shape and pose space is not affected by this operations.

  25. def transitionToSingleObject(reference: DomainWithPoseAndIntensity[_3D, DDomain], logExpMapping: PoseExpLogMappingSingleDomain[DDomain]): ShapePoseAndIntensityPGA[DDomain]

    Returns a marginal MultiBodyShapePoseAndIntensityPGA, which a ShapePoseAndIntensityPGA.

    Returns a marginal MultiBodyShapePoseAndIntensityPGA, which a ShapePoseAndIntensityPGA. It models deformations only on the given DomainWithPoseAndIntensity This method by marginalising over a single body domain return a shape and pose model a single body object.

  26. final def wait(): Unit
    Definition Classes
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    @throws(classOf[java.lang.InterruptedException])
  27. final def wait(arg0: Long, arg1: Int): Unit
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    @throws(classOf[java.lang.InterruptedException])
  28. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException]) @native()

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