Class

toolkit.computervision.motion

OpticFlowPolynomial

Related Doc: package motion

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class OpticFlowPolynomial extends AnyRef

Multi-scale optic flow using the algorithm described in "Two-frame motion estimation based on polynomial expansion" by G. Farneback.

This lacks a segmentation component, so boundaries are quite blurred. The output is obtained from flow.

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Instance Constructors

  1. new OpticFlowPolynomial(image: libcog.ScalarField)

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    image

    Input image stream to be analyzed.

Value Members

  1. final def !=(arg0: Any): Boolean

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  2. final def ##(): Int

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  3. final def ==(arg0: Any): Boolean

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  4. object LocalGaussianKernel

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    Local version of GaussianKernel that produces a Matrix.

    Local version of GaussianKernel that produces a Matrix.

    The standard library version of GaussianKernel is set up to produce a ScalarField. PolynomialExpansion and PolynomialKernels can't work with a Gaussian in this format, however. This local object is here to simplify porting.

    -Ben

  5. final def asInstanceOf[T0]: T0

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  6. def clone(): AnyRef

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  7. final def eq(arg0: AnyRef): Boolean

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  8. def equals(arg0: Any): Boolean

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  9. def finalize(): Unit

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  10. val flow: libcog.VectorField

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    Output flow field.

  11. final def getClass(): Class[_]

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  12. def hashCode(): Int

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  13. final def isInstanceOf[T0]: Boolean

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  14. final def ne(arg0: AnyRef): Boolean

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  15. final def notify(): Unit

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  16. final def notifyAll(): Unit

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  17. val pyramid: GaussianPyramid

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  18. final def synchronized[T0](arg0: ⇒ T0): T0

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  19. def toString(): String

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  20. final def wait(): Unit

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  21. final def wait(arg0: Long, arg1: Int): Unit

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  22. final def wait(arg0: Long): Unit

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