class cv::SparseOpticalFlow

Overview

Base interface for sparse optical flow algorithms. More…

#include <tracking.hpp>

class SparseOpticalFlow: public cv::Algorithm
{
public:
    // methods

    virtual
    void
    calc(
        InputArray prevImg,
        InputArray nextImg,
        InputArray prevPts,
        InputOutputArray nextPts,
        OutputArray status,
        OutputArray err = cv::noArray()
        ) = 0;
};

// direct descendants

class SparsePyrLKOpticalFlow;

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);

protected:
    // methods

    void
    writeFormat(FileStorage& fs) const;

Detailed Documentation

Base interface for sparse optical flow algorithms.

Methods

virtual
void
calc(
    InputArray prevImg,
    InputArray nextImg,
    InputArray prevPts,
    InputOutputArray nextPts,
    OutputArray status,
    OutputArray err = cv::noArray()
    ) = 0

Calculates a sparse optical flow.

Parameters:

prevImg	First input image.
nextImg	Second input image of the same size and the same type as prevImg.
prevPts	Vector of 2D points for which the flow needs to be found.
nextPts	Output vector of 2D points containing the calculated new positions of input features in the second image.
status	Output status vector. Each element of the vector is set to 1 if the flow for the corresponding features has been found. Otherwise, it is set to 0.
err	Optional output vector that contains error response for each point (inverse confidence).