include/opencv2/stitching/detail/motion_estimators.hpp

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#ifndef __OPENCV_STITCHING_MOTION_ESTIMATORS_HPP__
#define __OPENCV_STITCHING_MOTION_ESTIMATORS_HPP__

#include "opencv2/core/core.hpp"
#include "matchers.hpp"
#include "util.hpp"
#include "camera.hpp"

namespace cv {
namespace detail {

class CV_EXPORTS Estimator
{
public:
    virtual ~Estimator() {}

    void operator ()(const std::vector<ImageFeatures> &features, const std::vector<MatchesInfo> &pairwise_matches,
                     std::vector<CameraParams> &cameras)
        { estimate(features, pairwise_matches, cameras); }

protected:
    virtual void estimate(const std::vector<ImageFeatures> &features, const std::vector<MatchesInfo> &pairwise_matches,
                          std::vector<CameraParams> &cameras) = 0;
};


class CV_EXPORTS HomographyBasedEstimator : public Estimator
{
public:
    HomographyBasedEstimator(bool is_focals_estimated = false)
        : is_focals_estimated_(is_focals_estimated) {}

private:
    void estimate(const std::vector<ImageFeatures> &features, const std::vector<MatchesInfo> &pairwise_matches,
                  std::vector<CameraParams> &cameras);

    bool is_focals_estimated_;
};


class CV_EXPORTS BundleAdjusterBase : public Estimator
{
public:
    const Mat refinementMask() const { return refinement_mask_.clone(); }
    void setRefinementMask(const Mat &mask)
    {
        CV_Assert(mask.type() == CV_8U && mask.size() == Size(3, 3));
        refinement_mask_ = mask.clone();
    }

    double confThresh() const { return conf_thresh_; }
    void setConfThresh(double conf_thresh) { conf_thresh_ = conf_thresh; }

    CvTermCriteria termCriteria() { return term_criteria_; }
    void setTermCriteria(const CvTermCriteria& term_criteria) { term_criteria_ = term_criteria; }

protected:
    BundleAdjusterBase(int num_params_per_cam, int num_errs_per_measurement)
        : num_params_per_cam_(num_params_per_cam),
          num_errs_per_measurement_(num_errs_per_measurement)
    {
        setRefinementMask(Mat::ones(3, 3, CV_8U));
        setConfThresh(1.);
        setTermCriteria(cvTermCriteria(CV_TERMCRIT_EPS + CV_TERMCRIT_ITER, 1000, DBL_EPSILON));
    }

    // Runs bundle adjustment
    virtual void estimate(const std::vector<ImageFeatures> &features,
                          const std::vector<MatchesInfo> &pairwise_matches,
                          std::vector<CameraParams> &cameras);

    virtual void setUpInitialCameraParams(const std::vector<CameraParams> &cameras) = 0;
    virtual void obtainRefinedCameraParams(std::vector<CameraParams> &cameras) const = 0;
    virtual void calcError(Mat &err) = 0;
    virtual void calcJacobian(Mat &jac) = 0;

    // 3x3 8U mask, where 0 means don't refine respective parameter, != 0 means refine
    Mat refinement_mask_;

    int num_images_;
    int total_num_matches_;

    int num_params_per_cam_;
    int num_errs_per_measurement_;

    const ImageFeatures *features_;
    const MatchesInfo *pairwise_matches_;

    // Threshold to filter out poorly matched image pairs
    double conf_thresh_;

    //Levenberg–Marquardt algorithm termination criteria
    CvTermCriteria term_criteria_;

    // Camera parameters matrix (CV_64F)
    Mat cam_params_;

    // Connected images pairs
    std::vector<std::pair<int,int> > edges_;
};


// Minimizes reprojection error.
// It can estimate focal length, aspect ratio, principal point.
// You can affect only on them via the refinement mask.
class CV_EXPORTS BundleAdjusterReproj : public BundleAdjusterBase
{
public:
    BundleAdjusterReproj() : BundleAdjusterBase(7, 2) {}

private:
    void setUpInitialCameraParams(const std::vector<CameraParams> &cameras);
    void obtainRefinedCameraParams(std::vector<CameraParams> &cameras) const;
    void calcError(Mat &err);
    void calcJacobian(Mat &jac);

    Mat err1_, err2_;
};


// Minimizes sun of ray-to-ray distances.
// It can estimate focal length. It ignores the refinement mask for now.
class CV_EXPORTS BundleAdjusterRay : public BundleAdjusterBase
{
public:
    BundleAdjusterRay() : BundleAdjusterBase(4, 3) {}

private:
    void setUpInitialCameraParams(const std::vector<CameraParams> &cameras);
    void obtainRefinedCameraParams(std::vector<CameraParams> &cameras) const;
    void calcError(Mat &err);
    void calcJacobian(Mat &jac);

    Mat err1_, err2_;
};


enum WaveCorrectKind
{
    WAVE_CORRECT_HORIZ,
    WAVE_CORRECT_VERT
};

void CV_EXPORTS waveCorrect(std::vector<Mat> &rmats, WaveCorrectKind kind);


// Auxiliary functions

// Returns matches graph representation in DOT language
std::string CV_EXPORTS matchesGraphAsString(std::vector<std::string> &pathes, std::vector<MatchesInfo> &pairwise_matches,
                                            float conf_threshold);

std::vector<int> CV_EXPORTS leaveBiggestComponent(std::vector<ImageFeatures> &features, std::vector<MatchesInfo> &pairwise_matches,
                                                  float conf_threshold);

void CV_EXPORTS findMaxSpanningTree(int num_images, const std::vector<MatchesInfo> &pairwise_matches,
                                    Graph &span_tree, std::vector<int> &centers);

} // namespace detail
} // namespace cv

#endif // __OPENCV_STITCHING_MOTION_ESTIMATORS_HPP__