Optical Flow
Note
- A general optical flow example can be found at opencv_source_code/samples/gpu/optical_flow.cpp
- A general optical flow example using the Nvidia API can be found at opencv_source_code/samples/gpu/opticalflow_nvidia_api.cpp
cuda::BroxOpticalFlow
Class computing the optical flow for two images using Brox et al Optical Flow algorithm ([Brox2004]).
class BroxOpticalFlow
{
public:
BroxOpticalFlow(float alpha_, float gamma_, float scale_factor_, int inner_iterations_, int outer_iterations_, int 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;
};
Note
- An example illustrating the Brox et al optical flow algorithm can be found at opencv_source_code/samples/gpu/brox_optical_flow.cpp
cuda::FarnebackOpticalFlow
Class computing a dense optical flow using the Gunnar Farneback’s algorithm.
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();
private:
/* hidden */
};
cuda::FarnebackOpticalFlow::operator ()
Computes a dense optical flow using the Gunnar Farneback’s algorithm.
cuda::FarnebackOpticalFlow::releaseMemory
Releases unused auxiliary memory buffers.
cuda::PyrLKOpticalFlow
Class used for calculating an optical flow.
class 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);
Size winSize;
int maxLevel;
int iters;
bool useInitialFlow;
void releaseMemory();
};
The class can calculate an optical flow for a sparse feature set or dense optical flow using the iterative Lucas-Kanade method with pyramids.
Note
- An example of the Lucas Kanade optical flow algorithm can be found at opencv_source_code/samples/gpu/pyrlk_optical_flow.cpp
cuda::PyrLKOpticalFlow::sparse
Calculate an optical flow for a sparse feature set.
cuda::PyrLKOpticalFlow::dense
Calculate dense optical flow.
cuda::PyrLKOpticalFlow::releaseMemory
Releases inner buffers memory.
cuda::interpolateFrames
Interpolates frames (images) using provided optical flow (displacement field).
| [Brox2004] |
|