/*M/////////////////////////////////////////////////////////////////////////////////////// // // IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. // // By downloading, copying, installing or using the software you agree to this license. // If you do not agree to this license, do not download, install, // copy or use the software. // // // License Agreement // For Open Source Computer Vision Library // // Copyright (C) 2000-2008, Intel Corporation, all rights reserved. // Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved. // Third party copyrights are property of their respective owners. // // Redistribution and use in source and binary forms, with or without modification, // are permitted provided that the following conditions are met: // // * Redistribution's of source code must retain the above copyright notice, // this list of conditions and the following disclaimer. // // * Redistribution's in binary form must reproduce the above copyright notice, // this list of conditions and the following disclaimer in the documentation // and/or other materials provided with the distribution. // // * The name of the copyright holders may not be used to endorse or promote products // derived from this software without specific prior written permission. // // This software is provided by the copyright holders and contributors "as is" and // any express or implied warranties, including, but not limited to, the implied // warranties of merchantability and fitness for a particular purpose are disclaimed. // In no event shall the Intel Corporation or contributors be liable for any direct, // indirect, incidental, special, exemplary, or consequential damages // (including, but not limited to, procurement of substitute goods or services; // 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_VIDEOSTAB_GLOBAL_MOTION_HPP__ #define __OPENCV_VIDEOSTAB_GLOBAL_MOTION_HPP__ #include <vector> #include <fstream> #include "opencv2/core.hpp" #include "opencv2/features2d.hpp" #include "opencv2/opencv_modules.hpp" #include "opencv2/videostab/optical_flow.hpp" #include "opencv2/videostab/motion_core.hpp" #include "opencv2/videostab/outlier_rejection.hpp" #ifdef HAVE_OPENCV_CUDAIMGPROC # include "opencv2/cudaimgproc.hpp" #endif namespace cv { namespace videostab { //! @addtogroup videostab_motion //! @{ /** @brief Estimates best global motion between two 2D point clouds in the least-squares sense. @note Works in-place and changes input point arrays. @param points0 Source set of 2D points (32F). @param points1 Destination set of 2D points (32F). @param model Motion model (up to MM_AFFINE). @param rmse Final root-mean-square error. @return 3x3 2D transformation matrix (32F). */ CV_EXPORTS Mat estimateGlobalMotionLeastSquares( InputOutputArray points0, InputOutputArray points1, int model = MM_AFFINE, float *rmse = 0); /** @brief Estimates best global motion between two 2D point clouds robustly (using RANSAC method). @param points0 Source set of 2D points (32F). @param points1 Destination set of 2D points (32F). @param model Motion model. See cv::videostab::MotionModel. @param params RANSAC method parameters. See videostab::RansacParams. @param rmse Final root-mean-square error. @param ninliers Final number of inliers. */ CV_EXPORTS Mat estimateGlobalMotionRansac( InputArray points0, InputArray points1, int model = MM_AFFINE, const RansacParams ¶ms = RansacParams::default2dMotion(MM_AFFINE), float *rmse = 0, int *ninliers = 0); /** @brief Base class for all global motion estimation methods. */ class CV_EXPORTS MotionEstimatorBase { public: virtual ~MotionEstimatorBase() {} /** @brief Sets motion model. @param val Motion model. See cv::videostab::MotionModel. */ virtual void setMotionModel(MotionModel val) { motionModel_ = val; } /** @return Motion model. See cv::videostab::MotionModel. */ virtual MotionModel motionModel() const { return motionModel_; } /** @brief Estimates global motion between two 2D point clouds. @param points0 Source set of 2D points (32F). @param points1 Destination set of 2D points (32F). @param ok Indicates whether motion was estimated successfully. @return 3x3 2D transformation matrix (32F). */ virtual Mat estimate(InputArray points0, InputArray points1, bool *ok = 0) = 0; protected: MotionEstimatorBase(MotionModel model) { setMotionModel(model); } private: MotionModel motionModel_; }; /** @brief Describes a robust RANSAC-based global 2D motion estimation method which minimizes L2 error. */ class CV_EXPORTS MotionEstimatorRansacL2 : public MotionEstimatorBase { public: MotionEstimatorRansacL2(MotionModel model = MM_AFFINE); void setRansacParams(const RansacParams &val) { ransacParams_ = val; } RansacParams ransacParams() const { return ransacParams_; } void setMinInlierRatio(float val) { minInlierRatio_ = val; } float minInlierRatio() const { return minInlierRatio_; } virtual Mat estimate(InputArray points0, InputArray points1, bool *ok = 0); private: RansacParams ransacParams_; float minInlierRatio_; }; /** @brief Describes a global 2D motion estimation method which minimizes L1 error. @note To be able to use this method you must build OpenCV with CLP library support. : */ class CV_EXPORTS MotionEstimatorL1 : public MotionEstimatorBase { public: MotionEstimatorL1(MotionModel model = MM_AFFINE); virtual Mat estimate(InputArray points0, InputArray points1, bool *ok = 0); private: std::vector<double> obj_, collb_, colub_; std::vector<double> elems_, rowlb_, rowub_; std::vector<int> rows_, cols_; void set(int row, int col, double coef) { rows_.push_back(row); cols_.push_back(col); elems_.push_back(coef); } }; /** @brief Base class for global 2D motion estimation methods which take frames as input. */ class CV_EXPORTS ImageMotionEstimatorBase { public: virtual ~ImageMotionEstimatorBase() {} virtual void setMotionModel(MotionModel val) { motionModel_ = val; } virtual MotionModel motionModel() const { return motionModel_; } virtual Mat estimate(const Mat &frame0, const Mat &frame1, bool *ok = 0) = 0; protected: ImageMotionEstimatorBase(MotionModel model) { setMotionModel(model); } private: MotionModel motionModel_; }; class CV_EXPORTS FromFileMotionReader : public ImageMotionEstimatorBase { public: FromFileMotionReader(const String &path); virtual Mat estimate(const Mat &frame0, const Mat &frame1, bool *ok = 0); private: std::ifstream file_; }; class CV_EXPORTS ToFileMotionWriter : public ImageMotionEstimatorBase { public: ToFileMotionWriter(const String &path, Ptr<ImageMotionEstimatorBase> estimator); virtual void setMotionModel(MotionModel val) { motionEstimator_->setMotionModel(val); } virtual MotionModel motionModel() const { return motionEstimator_->motionModel(); } virtual Mat estimate(const Mat &frame0, const Mat &frame1, bool *ok = 0); private: std::ofstream file_; Ptr<ImageMotionEstimatorBase> motionEstimator_; }; /** @brief Describes a global 2D motion estimation method which uses keypoints detection and optical flow for matching. */ class CV_EXPORTS KeypointBasedMotionEstimator : public ImageMotionEstimatorBase { public: KeypointBasedMotionEstimator(Ptr<MotionEstimatorBase> estimator); virtual void setMotionModel(MotionModel val) { motionEstimator_->setMotionModel(val); } virtual MotionModel motionModel() const { return motionEstimator_->motionModel(); } void setDetector(Ptr<FeatureDetector> val) { detector_ = val; } Ptr<FeatureDetector> detector() const { return detector_; } void setOpticalFlowEstimator(Ptr<ISparseOptFlowEstimator> val) { optFlowEstimator_ = val; } Ptr<ISparseOptFlowEstimator> opticalFlowEstimator() const { return optFlowEstimator_; } void setOutlierRejector(Ptr<IOutlierRejector> val) { outlierRejector_ = val; } Ptr<IOutlierRejector> outlierRejector() const { return outlierRejector_; } virtual Mat estimate(const Mat &frame0, const Mat &frame1, bool *ok = 0); private: Ptr<MotionEstimatorBase> motionEstimator_; Ptr<FeatureDetector> detector_; Ptr<ISparseOptFlowEstimator> optFlowEstimator_; Ptr<IOutlierRejector> outlierRejector_; std::vector<uchar> status_; std::vector<KeyPoint> keypointsPrev_; std::vector<Point2f> pointsPrev_, points_; std::vector<Point2f> pointsPrevGood_, pointsGood_; }; #if defined(HAVE_OPENCV_CUDAIMGPROC) && defined(HAVE_OPENCV_CUDAOPTFLOW) class CV_EXPORTS KeypointBasedMotionEstimatorGpu : public ImageMotionEstimatorBase { public: KeypointBasedMotionEstimatorGpu(Ptr<MotionEstimatorBase> estimator); virtual void setMotionModel(MotionModel val) { motionEstimator_->setMotionModel(val); } virtual MotionModel motionModel() const { return motionEstimator_->motionModel(); } void setOutlierRejector(Ptr<IOutlierRejector> val) { outlierRejector_ = val; } Ptr<IOutlierRejector> outlierRejector() const { return outlierRejector_; } virtual Mat estimate(const Mat &frame0, const Mat &frame1, bool *ok = 0); Mat estimate(const cuda::GpuMat &frame0, const cuda::GpuMat &frame1, bool *ok = 0); private: Ptr<MotionEstimatorBase> motionEstimator_; Ptr<cuda::CornersDetector> detector_; SparsePyrLkOptFlowEstimatorGpu optFlowEstimator_; Ptr<IOutlierRejector> outlierRejector_; cuda::GpuMat frame0_, grayFrame0_, frame1_; cuda::GpuMat pointsPrev_, points_; cuda::GpuMat status_; Mat hostPointsPrev_, hostPoints_; std::vector<Point2f> hostPointsPrevTmp_, hostPointsTmp_; std::vector<uchar> rejectionStatus_; }; #endif // defined(HAVE_OPENCV_CUDAIMGPROC) && defined(HAVE_OPENCV_CUDAOPTFLOW) /** @brief Computes motion between two frames assuming that all the intermediate motions are known. @param from Source frame index. @param to Destination frame index. @param motions Pair-wise motions. motions[i] denotes motion from the frame i to the frame i+1 @return Motion from the frame from to the frame to. */ CV_EXPORTS Mat getMotion(int from, int to, const std::vector<Mat> &motions); //! @} } // namespace videostab } // namespace cv #endif