DIS optical flow algorithm. More...

#include <opencv2/video/tracking.hpp>

Inheritance diagram for cv::DISOpticalFlow:

Collaboration diagram for cv::DISOpticalFlow:

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

Public Member Functions
virtual void	calc (InputArray I0, InputArray I1, InputOutputArray flow)=0
	Calculates an optical flow. More...

virtual void	clear ()
	Clears the algorithm state. More...

virtual void	collectGarbage ()=0
	Releases all inner buffers. More...

virtual bool	empty () const
	Returns true if the Algorithm is empty (e.g. More...

virtual String	getDefaultName () const
	Returns the algorithm string identifier. More...

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). More...

virtual int	getGradientDescentIterations () const =0
	Maximum number of gradient descent iterations in the patch inverse search stage. More...

virtual int	getPatchSize () const =0
	Size of an image patch for matching (in pixels). More...

virtual int	getPatchStride () const =0
	Stride between neighbor patches. More...

virtual bool	getUseMeanNormalization () const =0
	Whether to use mean-normalization of patches when computing patch distance. More...

virtual bool	getUseSpatialPropagation () const =0
	Whether to use spatial propagation of good optical flow vectors. More...

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

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

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

virtual int	getVariationalRefinementIterations () const =0
	Number of fixed point iterations of variational refinement per scale. More...

virtual void	read (const FileNode &fn)
	Reads algorithm parameters from a file storage. More...

virtual void	save (const String &filename) const
	Saves the algorithm to a file. More...

virtual void	setFinestScale (int val)=0
	Finest level of the Gaussian pyramid on which the flow is computed (zero level corresponds to the original image resolution). More...

virtual void	setGradientDescentIterations (int val)=0
	Maximum number of gradient descent iterations in the patch inverse search stage. More...

virtual void	setPatchSize (int val)=0
	Size of an image patch for matching (in pixels). More...

virtual void	setPatchStride (int val)=0
	Stride between neighbor patches. More...

virtual void	setUseMeanNormalization (bool val)=0
	Whether to use mean-normalization of patches when computing patch distance. More...

virtual void	setUseSpatialPropagation (bool val)=0
	Whether to use spatial propagation of good optical flow vectors. More...

virtual void	setVariationalRefinementAlpha (float val)=0
	Weight of the smoothness term. More...

virtual void	setVariationalRefinementDelta (float val)=0
	Weight of the color constancy term. More...

virtual void	setVariationalRefinementGamma (float val)=0
	Weight of the gradient constancy term. More...

virtual void	setVariationalRefinementIterations (int val)=0
	Maximum number of gradient descent iterations in the patch inverse search stage. More...

virtual void	write (FileStorage &fs) const
	Stores algorithm parameters in a file storage. More...

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

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

template<typename _Tp >
static Ptr< _Tp >	load (const String &filename, const String &objname=String())
	Loads algorithm from the file. More...

template<typename _Tp >
static Ptr< _Tp >	loadFromString (const String &strModel, const String &objname=String())
	Loads algorithm from a String. More...

template<typename _Tp >
static Ptr< _Tp >	read (const FileNode &fn)
	Reads algorithm from the file node. More...

Protected Member Functions
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 at [50] . 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

anonymous enum

Enumerator
PRESET_ULTRAFAST
PRESET_FAST
PRESET_MEDIUM

Member Function Documentation

◆ calc()

virtual void cv::DenseOpticalFlow::calc	(	InputArray	I0,
		InputArray	I1,
		InputOutputArray	flow
	)

pure virtualinherited

Calculates an optical flow.

Parameters

I0	first 8-bit single-channel input image.
I1	second input image of the same size and the same type as prev.
flow	computed flow image that has the same size as prev and type CV_32FC2.

◆ clear()

virtual void cv::Algorithm::clear ( )

inlinevirtualinherited

Clears the algorithm state.

Reimplemented in cv::FlannBasedMatcher, and cv::DescriptorMatcher.

◆ collectGarbage()

virtual void cv::DenseOpticalFlow::collectGarbage ( )

pure virtualinherited

Releases all inner buffers.

◆ create()

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

static

Creates an instance of DISOpticalFlow.

Parameters

preset one of PRESET_ULTRAFAST, PRESET_FAST and PRESET_MEDIUM

◆ empty()

virtual bool cv::Algorithm::empty ( ) const

inlinevirtualinherited

Returns true if the Algorithm is empty (e.g.

in the very beginning or after unsuccessful read

Reimplemented in cv::DescriptorMatcher, cv::ml::StatModel, cv::Feature2D, and cv::BaseCascadeClassifier.

◆ getDefaultName()

virtual String cv::Algorithm::getDefaultName ( ) const

virtualinherited

Returns the algorithm string identifier.

This string is used as top level xml/yml node tag when the object is saved to a file or string.

Reimplemented in cv::AKAZE, cv::KAZE, cv::SimpleBlobDetector, cv::GFTTDetector, cv::AgastFeatureDetector, cv::FastFeatureDetector, cv::MSER, cv::ORB, cv::BRISK, and cv::Feature2D.

◆ getFinestScale()

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

pure virtual

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

◆ getGradientDescentIterations()

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

pure virtual

Maximum number of gradient descent iterations in the patch inverse search stage.

Higher values may improve quality in some cases.

See also: setGradientDescentIterations

◆ getPatchSize()

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

pure virtual

Size of an image patch for matching (in pixels).

Normally, default 8x8 patches work well enough in most cases.

See also: setPatchSize

◆ getPatchStride()

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

pure virtual

Stride between neighbor patches.

Must be less than patch size. Lower values correspond to higher flow quality.

See also: setPatchStride

◆ getUseMeanNormalization()

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

pure virtual

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

◆ getUseSpatialPropagation()

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

pure virtual

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

◆ getVariationalRefinementAlpha()

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

pure virtual

Weight of the smoothness term.

See also: setVariationalRefinementAlpha

◆ getVariationalRefinementDelta()

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

pure virtual

Weight of the color constancy term.

See also: setVariationalRefinementDelta

◆ getVariationalRefinementGamma()

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

pure virtual

Weight of the gradient constancy term.

See also: setVariationalRefinementGamma

◆ getVariationalRefinementIterations()

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

pure virtual

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

◆ load()

template<typename _Tp >

static Ptr<_Tp> cv::Algorithm::load	(	const String &	filename,
		const String &	objname = `String()`
	)

inlinestaticinherited

Loads algorithm from the file.

Parameters

filename	Name of the file to read.
objname	The optional name of the node to read (if empty, the first top-level node will be used)

This is static template method of Algorithm. It's usage is following (in the case of SVM):

Ptr<SVM> svm = Algorithm::load<SVM>("my_svm_model.xml");

In order to make this method work, the derived class must overwrite Algorithm::read(const FileNode& fn).

References CV_Assert, cv::FileNode::empty(), cv::FileStorage::getFirstTopLevelNode(), cv::FileStorage::isOpened(), and cv::FileStorage::READ.

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◆ loadFromString()

template<typename _Tp >

static Ptr<_Tp> cv::Algorithm::loadFromString	(	const String &	strModel,
		const String &	objname = `String()`
	)

inlinestaticinherited

Loads algorithm from a String.

Parameters

strModel	The string variable containing the model you want to load.
objname	The optional name of the node to read (if empty, the first top-level node will be used)

This is static template method of Algorithm. It's usage is following (in the case of SVM):

Ptr<SVM> svm = Algorithm::loadFromString<SVM>(myStringModel);

References CV_WRAP, cv::FileNode::empty(), cv::FileStorage::getFirstTopLevelNode(), cv::FileStorage::MEMORY, and cv::FileStorage::READ.

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◆ read() [1/2]

virtual void cv::Algorithm::read ( const FileNode & fn )

inlinevirtualinherited

Reads algorithm parameters from a file storage.

Reimplemented in cv::FlannBasedMatcher, cv::DescriptorMatcher, and cv::Feature2D.

◆ read() [2/2]

template<typename _Tp >

static Ptr<_Tp> cv::Algorithm::read ( const FileNode & fn )

inlinestaticinherited

Reads algorithm from the file node.

This is static template method of Algorithm. It's usage is following (in the case of SVM):

cv::FileStorage fsRead("example.xml", FileStorage::READ);

Ptr<SVM> svm = Algorithm::read<SVM>(fsRead.root());

In order to make this method work, the derived class must overwrite Algorithm::read(const FileNode& fn) and also have static create() method without parameters (or with all the optional parameters)

◆ save()

virtual void cv::Algorithm::save ( const String & filename ) const

virtualinherited

Saves the algorithm to a file.

In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

◆ setFinestScale()

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

pure virtual

Finest level of the Gaussian pyramid on which the flow is computed (zero level corresponds to the original image resolution).

See also: getFinestScale

◆ setGradientDescentIterations()

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

pure virtual

Maximum number of gradient descent iterations in the patch inverse search stage.

See also: getGradientDescentIterations

◆ setPatchSize()

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

pure virtual

Size of an image patch for matching (in pixels).

See also: getPatchSize

◆ setPatchStride()

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

pure virtual

Stride between neighbor patches.

See also: getPatchStride

◆ setUseMeanNormalization()

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

pure virtual

Whether to use mean-normalization of patches when computing patch distance.

See also: getUseMeanNormalization

◆ setUseSpatialPropagation()

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

pure virtual

Whether to use spatial propagation of good optical flow vectors.

See also: getUseSpatialPropagation

◆ setVariationalRefinementAlpha()

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

pure virtual

Weight of the smoothness term.

See also: getVariationalRefinementAlpha

◆ setVariationalRefinementDelta()

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

pure virtual

Weight of the color constancy term.

See also: getVariationalRefinementDelta

◆ setVariationalRefinementGamma()

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

pure virtual

Weight of the gradient constancy term.

See also: getVariationalRefinementGamma

◆ setVariationalRefinementIterations()

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

pure virtual

Maximum number of gradient descent iterations in the patch inverse search stage.

See also: getGradientDescentIterations

◆ write() [1/2]

virtual void cv::Algorithm::write ( FileStorage & fs ) const

inlinevirtualinherited

Stores algorithm parameters in a file storage.

Reimplemented in cv::FlannBasedMatcher, cv::DescriptorMatcher, and cv::Feature2D.

References CV_WRAP.

Referenced by cv::Feature2D::write(), and cv::DescriptorMatcher::write().

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◆ write() [2/2]

void cv::Algorithm::write	(	const Ptr< FileStorage > &	fs,
		const String &	name = `String()`
	)		const

inherited

simplified API for language bindings This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

◆ writeFormat()

void cv::Algorithm::writeFormat ( FileStorage & fs ) const

protectedinherited

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

opencv2/video/tracking.hpp

Public Types

Public Member Functions

Static Public Member Functions

Protected Member Functions

Detailed Description

Member Enumeration Documentation

◆ anonymous enum

Member Function Documentation

◆ calc()

◆ clear()

◆ collectGarbage()

◆ create()

◆ empty()

◆ getDefaultName()

◆ getFinestScale()

◆ getGradientDescentIterations()

◆ getPatchSize()

◆ getPatchStride()

◆ getUseMeanNormalization()

◆ getUseSpatialPropagation()

◆ getVariationalRefinementAlpha()

◆ getVariationalRefinementDelta()

◆ getVariationalRefinementGamma()

◆ getVariationalRefinementIterations()

◆ load()

◆ loadFromString()

◆ read() [1/2]

◆ read() [2/2]

◆ save()

◆ setFinestScale()

◆ setGradientDescentIterations()

◆ setPatchSize()

◆ setPatchStride()

◆ setUseMeanNormalization()

◆ setUseSpatialPropagation()

◆ setVariationalRefinementAlpha()

◆ setVariationalRefinementDelta()

◆ setVariationalRefinementGamma()

◆ setVariationalRefinementIterations()

◆ write() [1/2]

◆ write() [2/2]

◆ writeFormat()