mirror of
https://github.com/opencv/opencv.git
synced 2024-12-30 21:25:58 +08:00
312 lines
10 KiB
C++
312 lines
10 KiB
C++
/*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, 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_GPUOPTFLOW_HPP__
|
|
#define __OPENCV_GPUOPTFLOW_HPP__
|
|
|
|
#ifndef __cplusplus
|
|
# error gpuoptflow.hpp header must be compiled as C++
|
|
#endif
|
|
|
|
#include "opencv2/core/gpu.hpp"
|
|
|
|
namespace cv { namespace cuda {
|
|
|
|
class CV_EXPORTS BroxOpticalFlow
|
|
{
|
|
public:
|
|
BroxOpticalFlow(float alpha_, float gamma_, float scale_factor_, int inner_iterations_, int outer_iterations_, int solver_iterations_) :
|
|
alpha(alpha_), gamma(gamma_), scale_factor(scale_factor_),
|
|
inner_iterations(inner_iterations_), outer_iterations(outer_iterations_), solver_iterations(solver_iterations_)
|
|
{
|
|
}
|
|
|
|
//! Compute optical flow
|
|
//! frame0 - source frame (supports only CV_32FC1 type)
|
|
//! frame1 - frame to track (with the same size and type as frame0)
|
|
//! u - flow horizontal component (along x axis)
|
|
//! v - flow vertical component (along y axis)
|
|
void operator ()(const GpuMat& frame0, const GpuMat& frame1, GpuMat& u, GpuMat& v, Stream& stream = Stream::Null());
|
|
|
|
//! flow smoothness
|
|
float alpha;
|
|
|
|
//! gradient constancy importance
|
|
float gamma;
|
|
|
|
//! pyramid scale factor
|
|
float scale_factor;
|
|
|
|
//! number of lagged non-linearity iterations (inner loop)
|
|
int inner_iterations;
|
|
|
|
//! number of warping iterations (number of pyramid levels)
|
|
int outer_iterations;
|
|
|
|
//! number of linear system solver iterations
|
|
int solver_iterations;
|
|
|
|
GpuMat buf;
|
|
};
|
|
|
|
class CV_EXPORTS PyrLKOpticalFlow
|
|
{
|
|
public:
|
|
PyrLKOpticalFlow();
|
|
|
|
void sparse(const GpuMat& prevImg, const GpuMat& nextImg, const GpuMat& prevPts, GpuMat& nextPts,
|
|
GpuMat& status, GpuMat* err = 0);
|
|
|
|
void dense(const GpuMat& prevImg, const GpuMat& nextImg, GpuMat& u, GpuMat& v, GpuMat* err = 0);
|
|
|
|
void releaseMemory();
|
|
|
|
Size winSize;
|
|
int maxLevel;
|
|
int iters;
|
|
bool useInitialFlow;
|
|
|
|
private:
|
|
std::vector<GpuMat> prevPyr_;
|
|
std::vector<GpuMat> nextPyr_;
|
|
|
|
GpuMat buf_;
|
|
|
|
GpuMat uPyr_[2];
|
|
GpuMat vPyr_[2];
|
|
};
|
|
|
|
class CV_EXPORTS FarnebackOpticalFlow
|
|
{
|
|
public:
|
|
FarnebackOpticalFlow()
|
|
{
|
|
numLevels = 5;
|
|
pyrScale = 0.5;
|
|
fastPyramids = false;
|
|
winSize = 13;
|
|
numIters = 10;
|
|
polyN = 5;
|
|
polySigma = 1.1;
|
|
flags = 0;
|
|
}
|
|
|
|
int numLevels;
|
|
double pyrScale;
|
|
bool fastPyramids;
|
|
int winSize;
|
|
int numIters;
|
|
int polyN;
|
|
double polySigma;
|
|
int flags;
|
|
|
|
void operator ()(const GpuMat &frame0, const GpuMat &frame1, GpuMat &flowx, GpuMat &flowy, Stream &s = Stream::Null());
|
|
|
|
void releaseMemory()
|
|
{
|
|
frames_[0].release();
|
|
frames_[1].release();
|
|
pyrLevel_[0].release();
|
|
pyrLevel_[1].release();
|
|
M_.release();
|
|
bufM_.release();
|
|
R_[0].release();
|
|
R_[1].release();
|
|
blurredFrame_[0].release();
|
|
blurredFrame_[1].release();
|
|
pyramid0_.clear();
|
|
pyramid1_.clear();
|
|
}
|
|
|
|
private:
|
|
void prepareGaussian(
|
|
int n, double sigma, float *g, float *xg, float *xxg,
|
|
double &ig11, double &ig03, double &ig33, double &ig55);
|
|
|
|
void setPolynomialExpansionConsts(int n, double sigma);
|
|
|
|
void updateFlow_boxFilter(
|
|
const GpuMat& R0, const GpuMat& R1, GpuMat& flowx, GpuMat &flowy,
|
|
GpuMat& M, GpuMat &bufM, int blockSize, bool updateMatrices, Stream streams[]);
|
|
|
|
void updateFlow_gaussianBlur(
|
|
const GpuMat& R0, const GpuMat& R1, GpuMat& flowx, GpuMat& flowy,
|
|
GpuMat& M, GpuMat &bufM, int blockSize, bool updateMatrices, Stream streams[]);
|
|
|
|
GpuMat frames_[2];
|
|
GpuMat pyrLevel_[2], M_, bufM_, R_[2], blurredFrame_[2];
|
|
std::vector<GpuMat> pyramid0_, pyramid1_;
|
|
};
|
|
|
|
// Implementation of the Zach, Pock and Bischof Dual TV-L1 Optical Flow method
|
|
//
|
|
// see reference:
|
|
// [1] C. Zach, T. Pock and H. Bischof, "A Duality Based Approach for Realtime TV-L1 Optical Flow".
|
|
// [2] Javier Sanchez, Enric Meinhardt-Llopis and Gabriele Facciolo. "TV-L1 Optical Flow Estimation".
|
|
class CV_EXPORTS OpticalFlowDual_TVL1_GPU
|
|
{
|
|
public:
|
|
OpticalFlowDual_TVL1_GPU();
|
|
|
|
void operator ()(const GpuMat& I0, const GpuMat& I1, GpuMat& flowx, GpuMat& flowy);
|
|
|
|
void collectGarbage();
|
|
|
|
/**
|
|
* Time step of the numerical scheme.
|
|
*/
|
|
double tau;
|
|
|
|
/**
|
|
* Weight parameter for the data term, attachment parameter.
|
|
* This is the most relevant parameter, which determines the smoothness of the output.
|
|
* The smaller this parameter is, the smoother the solutions we obtain.
|
|
* It depends on the range of motions of the images, so its value should be adapted to each image sequence.
|
|
*/
|
|
double lambda;
|
|
|
|
/**
|
|
* Weight parameter for (u - v)^2, tightness parameter.
|
|
* It serves as a link between the attachment and the regularization terms.
|
|
* In theory, it should have a small value in order to maintain both parts in correspondence.
|
|
* The method is stable for a large range of values of this parameter.
|
|
*/
|
|
double theta;
|
|
|
|
/**
|
|
* Number of scales used to create the pyramid of images.
|
|
*/
|
|
int nscales;
|
|
|
|
/**
|
|
* Number of warpings per scale.
|
|
* Represents the number of times that I1(x+u0) and grad( I1(x+u0) ) are computed per scale.
|
|
* This is a parameter that assures the stability of the method.
|
|
* It also affects the running time, so it is a compromise between speed and accuracy.
|
|
*/
|
|
int warps;
|
|
|
|
/**
|
|
* Stopping criterion threshold used in the numerical scheme, which is a trade-off between precision and running time.
|
|
* A small value will yield more accurate solutions at the expense of a slower convergence.
|
|
*/
|
|
double epsilon;
|
|
|
|
/**
|
|
* Stopping criterion iterations number used in the numerical scheme.
|
|
*/
|
|
int iterations;
|
|
|
|
double scaleStep;
|
|
|
|
bool useInitialFlow;
|
|
|
|
private:
|
|
void procOneScale(const GpuMat& I0, const GpuMat& I1, GpuMat& u1, GpuMat& u2);
|
|
|
|
std::vector<GpuMat> I0s;
|
|
std::vector<GpuMat> I1s;
|
|
std::vector<GpuMat> u1s;
|
|
std::vector<GpuMat> u2s;
|
|
|
|
GpuMat I1x_buf;
|
|
GpuMat I1y_buf;
|
|
|
|
GpuMat I1w_buf;
|
|
GpuMat I1wx_buf;
|
|
GpuMat I1wy_buf;
|
|
|
|
GpuMat grad_buf;
|
|
GpuMat rho_c_buf;
|
|
|
|
GpuMat p11_buf;
|
|
GpuMat p12_buf;
|
|
GpuMat p21_buf;
|
|
GpuMat p22_buf;
|
|
|
|
GpuMat diff_buf;
|
|
GpuMat norm_buf;
|
|
};
|
|
|
|
//! Calculates optical flow for 2 images using block matching algorithm */
|
|
CV_EXPORTS void calcOpticalFlowBM(const GpuMat& prev, const GpuMat& curr,
|
|
Size block_size, Size shift_size, Size max_range, bool use_previous,
|
|
GpuMat& velx, GpuMat& vely, GpuMat& buf,
|
|
Stream& stream = Stream::Null());
|
|
|
|
class CV_EXPORTS FastOpticalFlowBM
|
|
{
|
|
public:
|
|
void operator ()(const GpuMat& I0, const GpuMat& I1, GpuMat& flowx, GpuMat& flowy, int search_window = 21, int block_window = 7, Stream& s = Stream::Null());
|
|
|
|
private:
|
|
GpuMat buffer;
|
|
GpuMat extended_I0;
|
|
GpuMat extended_I1;
|
|
};
|
|
|
|
//! Interpolate frames (images) using provided optical flow (displacement field).
|
|
//! frame0 - frame 0 (32-bit floating point images, single channel)
|
|
//! frame1 - frame 1 (the same type and size)
|
|
//! fu - forward horizontal displacement
|
|
//! fv - forward vertical displacement
|
|
//! bu - backward horizontal displacement
|
|
//! bv - backward vertical displacement
|
|
//! pos - new frame position
|
|
//! newFrame - new frame
|
|
//! buf - temporary buffer, will have width x 6*height size, CV_32FC1 type and contain 6 GpuMat;
|
|
//! occlusion masks 0, occlusion masks 1,
|
|
//! interpolated forward flow 0, interpolated forward flow 1,
|
|
//! interpolated backward flow 0, interpolated backward flow 1
|
|
//!
|
|
CV_EXPORTS void interpolateFrames(const GpuMat& frame0, const GpuMat& frame1,
|
|
const GpuMat& fu, const GpuMat& fv,
|
|
const GpuMat& bu, const GpuMat& bv,
|
|
float pos, GpuMat& newFrame, GpuMat& buf,
|
|
Stream& stream = Stream::Null());
|
|
|
|
CV_EXPORTS void createOpticalFlowNeedleMap(const GpuMat& u, const GpuMat& v, GpuMat& vertex, GpuMat& colors);
|
|
|
|
}} // namespace cv { namespace cuda {
|
|
|
|
#endif /* __OPENCV_GPUOPTFLOW_HPP__ */
|