case class MultiBodyShapeAndPosePGA[DDomain[D] <: DiscreteDomain[D]](gp: DiscreteLowRankGaussianProcess[_3D, [D]MultiBodyObject[D, DDomain], ShapeAndPoseVector[_3D]], logExpMapping: PoseExpLogMapping[DDomain])(implicit warperMBObject: DomainWarp[_3D, [D]MultiBodyObject[D, 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 MultiBodyShapeAndPosePGA while modelling shape deformation fields as StatisticalMeshModel, it uses PoseExpLogMapping to linearise pose deformation fields. MultiBodyShapeAndPosePGA warps the MultiBodyObject with the shape and pose deformation fields to produce a new MultiBodyObject.
- See also
DiscreteLowRankGaussianProcess
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- new MultiBodyShapeAndPosePGA(gp: DiscreteLowRankGaussianProcess[_3D, [D]MultiBodyObject[D, DDomain], ShapeAndPoseVector[_3D]], logExpMapping: PoseExpLogMapping[DDomain])(implicit warperMBObject: DomainWarp[_3D, [D]MultiBodyObject[D, DDomain]], warperInnerDomain: DomainWarp[_3D, DDomain], rng: Random)
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- val gp: DiscreteLowRankGaussianProcess[_3D, [D]MultiBodyObject[D, DDomain], ShapeAndPoseVector[_3D]]
- def instance(coeffs: DenseVector[Double]): MultiBodyObject[_3D, DDomain]
returns a MultiBodyObject that corresponds to a combination of the basis functions with the given coefficients coeffs.
returns a MultiBodyObject that corresponds to a combination of the basis functions with the given coefficients coeffs.
- See also
DiscreteLowRankGaussianProcess.instance
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- val logExpMapping: PoseExpLogMapping[DDomain]
- val mean: MultiBodyObject[_3D, DDomain]
The mean MultiBodyObject
The mean MultiBodyObject
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DiscreteLowRankGaussianProcess.mean
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- def newReference(newReference: MultiBodyObject[_3D, DDomain], interpolator: FieldInterpolator[_3D, [D]MultiBodyObject[D, DDomain], ShapeAndPoseVector[_3D]], newLogExpMapping: PoseExpLogMapping[DDomain]): MultiBodyShapeAndPosePGA[DDomain]
Warps the reference MultiBodyObject to a new reference MultiBodyObject.
Warps the reference MultiBodyObject to a new reference MultiBodyObject. The space spanned by the model is not affected.
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- def posterior(trainingData: List[IndexedSeq[(PointId, Point[_3D], MultivariateNormalDistribution)]]): MultiBodyShapeAndPosePGA[DDomain]
Similar to Point[_3D], Double)], but the training data is defined by specifying the target point instead of the displacement vector
- def posterior(trainingData: List[IndexedSeq[(PointId, Point[_3D])]], sigma2: Double): MultiBodyShapeAndPosePGA[DDomain]
Similar to Point[_3D])], sigma2: Double), but the training data is defined by specifying the target point instead of the displacement vector
- def productElementNames: Iterator[String]
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- def sample(): MultiBodyObject[_3D, DDomain]
draws a random MultiBodyObject.
draws a random MultiBodyObject.
- See also
DiscreteLowRankGaussianProcess.sample
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- def transform(rigidTransform: RigidTransformation[_3D]): MultiBodyShapeAndPosePGA[DDomain]
transform the MultiBodyShapeAndPosePGA using the given rigid transform.
transform the MultiBodyShapeAndPosePGA using the given rigid transform. The spanned shape and pose space is not affected by this operations.
- def transitionToSingleObject(reference: DomainWithPoseParameters[_3D, DDomain], logExpMapping: PoseExpLogMappingSingleDomain[DDomain])(implicit warper: DomainWarp[_3D, [D]DomainWithPoseParameters[D, DDomain]]): ShapeAndPosePGA[DDomain]
Returns a marginal MultiBodyShapeAndPosePGA, which a ShapeAndPosePGA.
Returns a marginal MultiBodyShapeAndPosePGA, which a ShapeAndPosePGA. It models deformations only on the given DomainWithPoseParameters This method by marginalising over a single body domain return a shape and pose model a single body object.
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