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