sustaining_gazes/lib/3rdParty/OpenCV3.1/include/opencv2/videostab/global_motion.hpp
2016-04-28 15:40:36 -04:00

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#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 &params = 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