class cv::DualTVL1OpticalFlow
Overview
“Dual TV L1” Optical Flow Algorithm. More…
#include <tracking.hpp> class DualTVL1OpticalFlow: public cv::DenseOpticalFlow { public: // methods virtual double getEpsilon() const = 0; virtual double getGamma() const = 0; virtual int getInnerIterations() const = 0; virtual double getLambda() const = 0; virtual int getMedianFiltering() const = 0; virtual int getOuterIterations() const = 0; virtual int getScalesNumber() const = 0; virtual double getScaleStep() const = 0; virtual double getTau() const = 0; virtual double getTheta() const = 0; virtual bool getUseInitialFlow() const = 0; virtual int getWarpingsNumber() const = 0; virtual void setEpsilon(double val) = 0; virtual void setGamma(double val) = 0; virtual void setInnerIterations(int val) = 0; virtual void setLambda(double val) = 0; virtual void setMedianFiltering(int val) = 0; virtual void setOuterIterations(int val) = 0; virtual void setScalesNumber(int val) = 0; virtual void setScaleStep(double val) = 0; virtual void setTau(double val) = 0; virtual void setTheta(double val) = 0; virtual void setUseInitialFlow(bool val) = 0; virtual void setWarpingsNumber(int val) = 0; static Ptr<DualTVL1OpticalFlow> create( double tau = 0.25, double lambda = 0.15, double theta = 0.3, int nscales = 5, int warps = 5, double epsilon = 0.01, int innnerIterations = 30, int outerIterations = 10, double scaleStep = 0.8, double gamma = 0.0, int medianFiltering = 5, bool useInitialFlow = false ); };
Inherited Members
public: // methods virtual void clear(); virtual bool empty() const; virtual String getDefaultName() const; virtual void read(const FileNode& fn); virtual void save(const String& filename) const; virtual void write(FileStorage& fs) const; template <typename _Tp> static Ptr<_Tp> load( const String& filename, const String& objname = String() ); template <typename _Tp> static Ptr<_Tp> loadFromString( const String& strModel, const String& objname = String() ); template <typename _Tp> static Ptr<_Tp> read(const FileNode& fn); virtual void calc( InputArray I0, InputArray I1, InputOutputArray flow ) = 0; virtual void collectGarbage() = 0; protected: // methods void writeFormat(FileStorage& fs) const;
Detailed Documentation
“Dual TV L1” Optical Flow Algorithm.
The class implements the “Dual TV L1” optical flow algorithm described in [95] and [75]. Here are important members of the class that control the algorithm, which you can set after constructing the class instance:
- member double tau Time step of the numerical scheme.
- member double lambda Weight parameter for the data term, attachment parameter. This is the most relevant parameter, which determines the smoothness of the output. The smaller this parameter is, the smoother the solutions we obtain. It depends on the range of motions of the images, so its value should be adapted to each image sequence.
- member double theta Weight parameter for (u - v)^2, tightness parameter. It serves as a link between the attachment and the regularization terms. In theory, it should have a small value in order to maintain both parts in correspondence. The method is stable for a large range of values of this parameter.
- member int nscales Number of scales used to create the pyramid of images.
- member int warps Number of warpings per scale. Represents the number of times that I1(x+u0) and grad( I1(x+u0) ) are computed per scale. This is a parameter that assures the stability of the method. It also affects the running time, so it is a compromise between speed and accuracy.
- member double epsilon Stopping criterion threshold used in the numerical scheme, which is a trade-off between precision and running time. A small value will yield more accurate solutions at the expense of a slower convergence.
- member int iterations Stopping criterion iterations number used in the numerical scheme.
- Zach, T. Pock and H. Bischof, “A Duality Based Approach for Realtime TV-L1 Optical Flow”. Javier Sanchez, Enric Meinhardt-Llopis and Gabriele Facciolo. “TV-L1 Optical Flow Estimation”.
Methods
virtual double getEpsilon() const = 0
Stopping criterion threshold used in the numerical scheme, which is a trade-off between precision and running time.
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virtual double getGamma() const = 0
coefficient for additional illumination variation term
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virtual int getInnerIterations() const = 0
Inner iterations (between outlier filtering) used in the numerical scheme.
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virtual double getLambda() const = 0
Weight parameter for the data term, attachment parameter.
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virtual int getMedianFiltering() const = 0
Median filter kernel size (1 = no filter) (3 or 5)
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virtual int getOuterIterations() const = 0
Outer iterations (number of inner loops) used in the numerical scheme.
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virtual int getScalesNumber() const = 0
Number of scales used to create the pyramid of images.
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virtual double getScaleStep() const = 0
Step between scales (<1)
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virtual double getTau() const = 0
Time step of the numerical scheme.
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virtual double getTheta() const = 0
Weight parameter for (u - v)^2, tightness parameter.
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virtual bool getUseInitialFlow() const = 0
Use initial flow.
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virtual int getWarpingsNumber() const = 0
Number of warpings per scale.
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virtual void setEpsilon(double val) = 0
Stopping criterion threshold used in the numerical scheme, which is a trade-off between precision and running time.
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virtual void setGamma(double val) = 0
coefficient for additional illumination variation term
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virtual void setInnerIterations(int val) = 0
Inner iterations (between outlier filtering) used in the numerical scheme.
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virtual void setLambda(double val) = 0
Weight parameter for the data term, attachment parameter.
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virtual void setMedianFiltering(int val) = 0
Median filter kernel size (1 = no filter) (3 or 5)
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virtual void setOuterIterations(int val) = 0
Outer iterations (number of inner loops) used in the numerical scheme.
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virtual void setScalesNumber(int val) = 0
Number of scales used to create the pyramid of images.
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virtual void setScaleStep(double val) = 0
Step between scales (<1)
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virtual void setTau(double val) = 0
Time step of the numerical scheme.
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virtual void setTheta(double val) = 0
Weight parameter for (u - v)^2, tightness parameter.
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virtual void setUseInitialFlow(bool val) = 0
Use initial flow.
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virtual void setWarpingsNumber(int val) = 0
Number of warpings per scale.
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static Ptr<DualTVL1OpticalFlow> create( double tau = 0.25, double lambda = 0.15, double theta = 0.3, int nscales = 5, int warps = 5, double epsilon = 0.01, int innnerIterations = 30, int outerIterations = 10, double scaleStep = 0.8, double gamma = 0.0, int medianFiltering = 5, bool useInitialFlow = false )
Creates instance of cv::DualTVL1OpticalFlow.