DeepFlow optical flow algorithm implementation
flow = cv.calcOpticalFlowDF(I0, I1)
Input
- I0 First 8-bit single-channel grayscale input image.
- I1 Second input image of the same size and type as
I0.
Output
- flow computed flow image that has the same size as
I0 and type
single (2-channels). Flow for (x,y) is stored in the third
dimension.
The class implements the DeepFlow optical flow algorithm described in
[Weinzaepfel2013]. See also http://lear.inrialpes.fr/src/deepmatching/ .
Parameters - class fields - are:
- Alpha Smoothness assumption weight. default 1.0
- Delta Color constancy assumption weight. default 0.5
- Gamma Gradient constancy weight. default 5.0
- Sigma Gaussian smoothing parameter. default 0.6
- MinSize Minimal dimension of an image in the pyramid (next, smaller
images in the pyramid are generated until one of the dimensions
reaches this size). default 25
- DownscaleFactor Scaling factor in the image pyramid (must be <1).
default 0.95
- FixedPointIterations How many iterations on each level of the pyramid.
default 5
- SorIterations Iterations of Succesive Over-Relaxation (solver).
default 25
- Omega Relaxation factor in SOR. default 1.6
References
[Weinzaepfel2013]:
Philippe Weinzaepfel, Jerome Revaud, Zaid Harchaoui, and Cordelia Schmid.
"Deepflow: Large displacement optical flow with deep matching".
In Computer Vision (ICCV), 2013 IEEE International Conference on,
pages 1385-1392. IEEE, 2013.