cv::VariationalRefinement Class Reference

Variational optical flow refinement. More...

#include <opencv2/video/tracking.hpp>

Collaboration diagram for cv::VariationalRefinement:

Public Member Functions
virtual void	calcUV (InputArray I0, InputArray I1, InputOutputArray flow_u, InputOutputArray flow_v)=0
	calc function overload to handle separate horizontal (u) and vertical (v) flow components (to avoid extra splits/merges)
virtual float	getAlpha () const =0
	Weight of the smoothness term.
virtual float	getDelta () const =0
	Weight of the color constancy term.
virtual float	getEpsilon () const =0
	Norm value shift for robust penalizer.
virtual int	getFixedPointIterations () const =0
	Number of outer (fixed-point) iterations in the minimization procedure.
virtual float	getGamma () const =0
	Weight of the gradient constancy term.
virtual float	getOmega () const =0
	Relaxation factor in SOR.
virtual int	getSorIterations () const =0
	Number of inner successive over-relaxation (SOR) iterations in the minimization procedure to solve the respective linear system.
virtual void	setAlpha (float val)=0
	Weight of the smoothness term.
virtual void	setDelta (float val)=0
	Weight of the color constancy term.
virtual void	setEpsilon (float val)=0
	Norm value shift for robust penalizer.
virtual void	setFixedPointIterations (int val)=0
	Number of outer (fixed-point) iterations in the minimization procedure.
virtual void	setGamma (float val)=0
	Weight of the gradient constancy term.
virtual void	setOmega (float val)=0
	Relaxation factor in SOR.
virtual void	setSorIterations (int val)=0
	Number of inner successive over-relaxation (SOR) iterations in the minimization procedure to solve the respective linear system.
Public Member Functions inherited from cv::DenseOpticalFlow
virtual void	calc (InputArray I0, InputArray I1, InputOutputArray flow)=0
	Calculates an optical flow.
virtual void	collectGarbage ()=0
	Releases all inner buffers.
Public Member Functions inherited from cv::Algorithm
	Algorithm ()
virtual	~Algorithm ()
virtual void	clear ()
	Clears the algorithm state.
virtual bool	empty () const
	Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read.
virtual String	getDefaultName () const
virtual void	read (const FileNode &fn)
	Reads algorithm parameters from a file storage.
virtual void	save (const String &filename) const
virtual void	write (FileStorage &fs) const
	Stores algorithm parameters in a file storage.
void	write (FileStorage &fs, const String &name) const

Static Public Member Functions
static Ptr< VariationalRefinement >	create ()
	Creates an instance of VariationalRefinement.
Static Public Member Functions inherited from cv::Algorithm
template<typename _Tp >
static Ptr< _Tp >	load (const String &filename, const String &objname=String())
	Loads algorithm from the file.
template<typename _Tp >
static Ptr< _Tp >	loadFromString (const String &strModel, const String &objname=String())
	Loads algorithm from a String.
template<typename _Tp >
static Ptr< _Tp >	read (const FileNode &fn)
	Reads algorithm from the file node.

Additional Inherited Members
Protected Member Functions inherited from cv::Algorithm
void	writeFormat (FileStorage &fs) const

Detailed Description

Variational optical flow refinement.

This class implements variational refinement of the input flow field, i.e. it uses input flow to initialize the minimization of the following functional: \(E(U) = \int_{\Omega} \delta \Psi(E_I) + \gamma \Psi(E_G) + \alpha \Psi(E_S) \), where \(E_I,E_G,E_S\) are color constancy, gradient constancy and smoothness terms respectively. \(\Psi(s^2)=\sqrt{s^2+\epsilon^2}\) is a robust penalizer to limit the influence of outliers. A complete formulation and a description of the minimization procedure can be found in [42]

Member Function Documentation

calcUV()

virtual void cv::VariationalRefinement::calcUV ( InputArray I0, InputArray I1, InputOutputArray flow_u, InputOutputArray flow_v )

pure virtual

Python:
	cv.VariationalRefinement.calcUV(	I0, I1, flow_u, flow_v	) ->	flow_u, flow_v

calc function overload to handle separate horizontal (u) and vertical (v) flow components (to avoid extra splits/merges)

create()

static Ptr< VariationalRefinement > cv::VariationalRefinement::create ( )

static

Python:
	cv.VariationalRefinement.create(		) ->	retval
	cv.VariationalRefinement_create(		) ->	retval

Creates an instance of VariationalRefinement.

getAlpha()

virtual float cv::VariationalRefinement::getAlpha ( ) const

pure virtual

Python:
	cv.VariationalRefinement.getAlpha(		) ->	retval

Weight of the smoothness term.

See also

setAlpha

getDelta()

virtual float cv::VariationalRefinement::getDelta ( ) const

pure virtual

Python:
	cv.VariationalRefinement.getDelta(		) ->	retval

Weight of the color constancy term.

See also

setDelta

getEpsilon()

virtual float cv::VariationalRefinement::getEpsilon ( ) const

pure virtual

Python:
	cv.VariationalRefinement.getEpsilon(		) ->	retval

Norm value shift for robust penalizer.

See also

setEpsilon

getFixedPointIterations()

virtual int cv::VariationalRefinement::getFixedPointIterations ( ) const

pure virtual

Python:
	cv.VariationalRefinement.getFixedPointIterations(		) ->	retval

Number of outer (fixed-point) iterations in the minimization procedure.

See also

setFixedPointIterations

getGamma()

virtual float cv::VariationalRefinement::getGamma ( ) const

pure virtual

Python:
	cv.VariationalRefinement.getGamma(		) ->	retval

Weight of the gradient constancy term.

See also

setGamma

getOmega()

virtual float cv::VariationalRefinement::getOmega ( ) const

pure virtual

Python:
	cv.VariationalRefinement.getOmega(		) ->	retval

Relaxation factor in SOR.

See also

setOmega

getSorIterations()

virtual int cv::VariationalRefinement::getSorIterations ( ) const

pure virtual

Python:
	cv.VariationalRefinement.getSorIterations(		) ->	retval

Number of inner successive over-relaxation (SOR) iterations in the minimization procedure to solve the respective linear system.

See also

setSorIterations

setAlpha()

virtual void cv::VariationalRefinement::setAlpha ( float val )

pure virtual

Python:
	cv.VariationalRefinement.setAlpha(	val	) ->	None

Weight of the smoothness term.

See also

getAlpha

setDelta()

virtual void cv::VariationalRefinement::setDelta ( float val )

pure virtual

Python:
	cv.VariationalRefinement.setDelta(	val	) ->	None

Weight of the color constancy term.

See also

getDelta

setEpsilon()

virtual void cv::VariationalRefinement::setEpsilon ( float val )

pure virtual

Python:
	cv.VariationalRefinement.setEpsilon(	val	) ->	None

Norm value shift for robust penalizer.

See also

getEpsilon

setFixedPointIterations()

virtual void cv::VariationalRefinement::setFixedPointIterations ( int val )

pure virtual

Python:
	cv.VariationalRefinement.setFixedPointIterations(	val	) ->	None

Number of outer (fixed-point) iterations in the minimization procedure.

See also

getFixedPointIterations

setGamma()

virtual void cv::VariationalRefinement::setGamma ( float val )

pure virtual

Python:
	cv.VariationalRefinement.setGamma(	val	) ->	None

Weight of the gradient constancy term.

See also

getGamma

setOmega()

virtual void cv::VariationalRefinement::setOmega ( float val )

pure virtual

Python:
	cv.VariationalRefinement.setOmega(	val	) ->	None

Relaxation factor in SOR.

See also

getOmega

setSorIterations()

virtual void cv::VariationalRefinement::setSorIterations ( int val )

pure virtual

Python:
	cv.VariationalRefinement.setSorIterations(	val	) ->	None

Number of inner successive over-relaxation (SOR) iterations in the minimization procedure to solve the respective linear system.

See also

getSorIterations

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The documentation for this class was generated from the following file:

• opencv2/video/tracking.hpp