DIS optical flow algorithm. More...

#include <opencv2/video/tracking.hpp>

Inheritance diagram for cv::DISOpticalFlow:

Public Types
enum	{ PRESET_ULTRAFAST = 0, PRESET_FAST = 1, PRESET_MEDIUM = 2 }

Public Member Functions
virtual int	getFinestScale () const =0
	Finest level of the Gaussian pyramid on which the flow is computed (zero level corresponds to the original image resolution). The final flow is obtained by bilinear upscaling.

virtual int	getGradientDescentIterations () const =0
	Maximum number of gradient descent iterations in the patch inverse search stage. Higher values may improve quality in some cases.

virtual int	getPatchSize () const =0
	Size of an image patch for matching (in pixels). Normally, default 8x8 patches work well enough in most cases.

virtual int	getPatchStride () const =0
	Stride between neighbor patches. Must be less than patch size. Lower values correspond to higher flow quality.

virtual bool	getUseMeanNormalization () const =0
	Whether to use mean-normalization of patches when computing patch distance. It is turned on by default as it typically provides a noticeable quality boost because of increased robustness to illumination variations. Turn it off if you are certain that your sequence doesn't contain any changes in illumination.

virtual bool	getUseSpatialPropagation () const =0
	Whether to use spatial propagation of good optical flow vectors. This option is turned on by default, as it tends to work better on average and can sometimes help recover from major errors introduced by the coarse-to-fine scheme employed by the DIS optical flow algorithm. Turning this option off can make the output flow field a bit smoother, however.

virtual float	getVariationalRefinementAlpha () const =0
	Weight of the smoothness term.

virtual float	getVariationalRefinementDelta () const =0
	Weight of the color constancy term.

virtual float	getVariationalRefinementGamma () const =0
	Weight of the gradient constancy term.

virtual int	getVariationalRefinementIterations () const =0
	Number of fixed point iterations of variational refinement per scale. Set to zero to disable variational refinement completely. Higher values will typically result in more smooth and high-quality flow.

virtual void	setFinestScale (int val)=0

virtual void	setGradientDescentIterations (int val)=0

virtual void	setPatchSize (int val)=0

virtual void	setPatchStride (int val)=0

virtual void	setUseMeanNormalization (bool val)=0

virtual void	setUseSpatialPropagation (bool val)=0

virtual void	setVariationalRefinementAlpha (float val)=0

virtual void	setVariationalRefinementDelta (float val)=0

virtual void	setVariationalRefinementGamma (float val)=0

virtual void	setVariationalRefinementIterations (int val)=0

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 (const Ptr< FileStorage > &fs, const String &name=String()) const
	simplified API for language bindingsThis is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

Static Public Member Functions
static Ptr< DISOpticalFlow >	create (int preset=DISOpticalFlow::PRESET_FAST)
	Creates an instance of DISOpticalFlow.

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

Detailed Description

DIS optical flow algorithm.

This class implements the Dense Inverse Search (DIS) optical flow algorithm. More details about the algorithm can be found atKroeger2016 . Includes three presets with preselected parameters to provide reasonable trade-off between speed and quality. However, even the slowest preset is still relatively fast, use DeepFlow if you need better quality and don't care about speed.

This implementation includes several additional features compared to the algorithm described in the paper, including spatial propagation of flow vectors (getUseSpatialPropagation), as well as an option to utilize an initial flow approximation passed to calc (which is, essentially, temporal propagation, if the previous frame's flow field is passed).

Member Enumeration Documentation

anonymous enum

Enumerator
PRESET_ULTRAFAST
PRESET_FAST
PRESET_MEDIUM

Member Function Documentation

static Ptr<DISOpticalFlow> cv::DISOpticalFlow::create ( int preset = DISOpticalFlow::PRESET_FAST )

static

Python:
	retval	=	cv.DISOpticalFlow_create(	[, preset]	)

Creates an instance of DISOpticalFlow.

Parameters

preset one of PRESET_ULTRAFAST, PRESET_FAST and PRESET_MEDIUM

virtual int cv::DISOpticalFlow::getFinestScale ( ) const

pure virtual

Python:
	retval	=	cv.DISOpticalFlow.getFinestScale(		)

Finest level of the Gaussian pyramid on which the flow is computed (zero level corresponds to the original image resolution). The final flow is obtained by bilinear upscaling.

See Also: setFinestScale

virtual int cv::DISOpticalFlow::getGradientDescentIterations ( ) const

pure virtual

Python:
	retval	=	cv.DISOpticalFlow.getGradientDescentIterations(		)

Maximum number of gradient descent iterations in the patch inverse search stage. Higher values may improve quality in some cases.

See Also: setGradientDescentIterations

virtual int cv::DISOpticalFlow::getPatchSize ( ) const

pure virtual

Python:
	retval	=	cv.DISOpticalFlow.getPatchSize(		)

Size of an image patch for matching (in pixels). Normally, default 8x8 patches work well enough in most cases.

See Also: setPatchSize

virtual int cv::DISOpticalFlow::getPatchStride ( ) const

pure virtual

Python:
	retval	=	cv.DISOpticalFlow.getPatchStride(		)

Stride between neighbor patches. Must be less than patch size. Lower values correspond to higher flow quality.

See Also: setPatchStride

virtual bool cv::DISOpticalFlow::getUseMeanNormalization ( ) const

pure virtual

Python:
	retval	=	cv.DISOpticalFlow.getUseMeanNormalization(		)

Whether to use mean-normalization of patches when computing patch distance. It is turned on by default as it typically provides a noticeable quality boost because of increased robustness to illumination variations. Turn it off if you are certain that your sequence doesn't contain any changes in illumination.

See Also: setUseMeanNormalization

virtual bool cv::DISOpticalFlow::getUseSpatialPropagation ( ) const

pure virtual

Python:
	retval	=	cv.DISOpticalFlow.getUseSpatialPropagation(		)

Whether to use spatial propagation of good optical flow vectors. This option is turned on by default, as it tends to work better on average and can sometimes help recover from major errors introduced by the coarse-to-fine scheme employed by the DIS optical flow algorithm. Turning this option off can make the output flow field a bit smoother, however.

See Also: setUseSpatialPropagation

virtual float cv::DISOpticalFlow::getVariationalRefinementAlpha ( ) const

pure virtual

Python:
	retval	=	cv.DISOpticalFlow.getVariationalRefinementAlpha(		)

Weight of the smoothness term.

See Also: setVariationalRefinementAlpha

virtual float cv::DISOpticalFlow::getVariationalRefinementDelta ( ) const

pure virtual

Python:
	retval	=	cv.DISOpticalFlow.getVariationalRefinementDelta(		)

Weight of the color constancy term.

See Also: setVariationalRefinementDelta

virtual float cv::DISOpticalFlow::getVariationalRefinementGamma ( ) const

pure virtual

Python:
	retval	=	cv.DISOpticalFlow.getVariationalRefinementGamma(		)

Weight of the gradient constancy term.

See Also: setVariationalRefinementGamma

virtual int cv::DISOpticalFlow::getVariationalRefinementIterations ( ) const

pure virtual

Python:
	retval	=	cv.DISOpticalFlow.getVariationalRefinementIterations(		)

Number of fixed point iterations of variational refinement per scale. Set to zero to disable variational refinement completely. Higher values will typically result in more smooth and high-quality flow.

See Also: setGradientDescentIterations

virtual void cv::DISOpticalFlow::setFinestScale ( int val )

pure virtual

Python:
	None	=	cv.DISOpticalFlow.setFinestScale(	val	)

Finest level of the Gaussian pyramid on which the flow is computed (zero level corresponds to the original image resolution). The final flow is obtained by bilinear upscaling.

See Also: getFinestScale

virtual void cv::DISOpticalFlow::setGradientDescentIterations ( int val )

pure virtual

Python:
	None	=	cv.DISOpticalFlow.setGradientDescentIterations(	val	)

Maximum number of gradient descent iterations in the patch inverse search stage. Higher values may improve quality in some cases.

See Also: getGradientDescentIterations

virtual void cv::DISOpticalFlow::setPatchSize ( int val )

pure virtual

Python:
	None	=	cv.DISOpticalFlow.setPatchSize(	val	)

Size of an image patch for matching (in pixels). Normally, default 8x8 patches work well enough in most cases.

See Also: getPatchSize

virtual void cv::DISOpticalFlow::setPatchStride ( int val )

pure virtual

Python:
	None	=	cv.DISOpticalFlow.setPatchStride(	val	)

Stride between neighbor patches. Must be less than patch size. Lower values correspond to higher flow quality.

See Also: getPatchStride

virtual void cv::DISOpticalFlow::setUseMeanNormalization ( bool val )

pure virtual

Python:
	None	=	cv.DISOpticalFlow.setUseMeanNormalization(	val	)

Whether to use mean-normalization of patches when computing patch distance. It is turned on by default as it typically provides a noticeable quality boost because of increased robustness to illumination variations. Turn it off if you are certain that your sequence doesn't contain any changes in illumination.

See Also: getUseMeanNormalization

virtual void cv::DISOpticalFlow::setUseSpatialPropagation ( bool val )

pure virtual

Python:
	None	=	cv.DISOpticalFlow.setUseSpatialPropagation(	val	)

Whether to use spatial propagation of good optical flow vectors. This option is turned on by default, as it tends to work better on average and can sometimes help recover from major errors introduced by the coarse-to-fine scheme employed by the DIS optical flow algorithm. Turning this option off can make the output flow field a bit smoother, however.

See Also: getUseSpatialPropagation

virtual void cv::DISOpticalFlow::setVariationalRefinementAlpha ( float val )

pure virtual

Python:
	None	=	cv.DISOpticalFlow.setVariationalRefinementAlpha(	val	)

Weight of the smoothness term.

See Also: getVariationalRefinementAlpha

virtual void cv::DISOpticalFlow::setVariationalRefinementDelta ( float val )

pure virtual

Python:
	None	=	cv.DISOpticalFlow.setVariationalRefinementDelta(	val	)

Weight of the color constancy term.

See Also: getVariationalRefinementDelta

virtual void cv::DISOpticalFlow::setVariationalRefinementGamma ( float val )

pure virtual

Python:
	None	=	cv.DISOpticalFlow.setVariationalRefinementGamma(	val	)

Weight of the gradient constancy term.

See Also: getVariationalRefinementGamma

virtual void cv::DISOpticalFlow::setVariationalRefinementIterations ( int val )

pure virtual

Python:
	None	=	cv.DISOpticalFlow.setVariationalRefinementIterations(	val	)

Maximum number of gradient descent iterations in the patch inverse search stage. Higher values may improve quality in some cases.

See Also: getGradientDescentIterations

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

modules/video/include/opencv2/video/tracking.hpp

Public Types

Public Member Functions

Static Public Member Functions

Additional Inherited Members

Detailed Description

Member Enumeration Documentation

Member Function Documentation