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// loss of use, data, or profits; or business interruption) however caused // and on any theory of liability, whether in contract, strict liability, // or tort (including negligence or otherwise) arising in any way out of // the use of this software, even if advised of the possibility of such damage. // //M*/ #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 &features, const std::vector &pairwise_matches, std::vector &cameras) { estimate(features, pairwise_matches, cameras); } protected: virtual void estimate(const std::vector &features, const std::vector &pairwise_matches, std::vector &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 &features, const std::vector &pairwise_matches, std::vector &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 &features, const std::vector &pairwise_matches, std::vector &cameras); virtual void setUpInitialCameraParams(const std::vector &cameras) = 0; virtual void obtainRefinedCameraParams(std::vector &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 > 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 &cameras); void obtainRefinedCameraParams(std::vector &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 &cameras); void obtainRefinedCameraParams(std::vector &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 &rmats, WaveCorrectKind kind); ////////////////////////////////////////////////////////////////////////////// // Auxiliary functions // Returns matches graph representation in DOT language std::string CV_EXPORTS matchesGraphAsString(std::vector &pathes, std::vector &pairwise_matches, float conf_threshold); std::vector CV_EXPORTS leaveBiggestComponent(std::vector &features, std::vector &pairwise_matches, float conf_threshold); void CV_EXPORTS findMaxSpanningTree(int num_images, const std::vector &pairwise_matches, Graph &span_tree, std::vector ¢ers); } // namespace detail } // namespace cv #endif // __OPENCV_STITCHING_MOTION_ESTIMATORS_HPP__