%CALCOPTICALFLOWFARNEBACK  Computes a dense optical flow using the Gunnar Farneback's algorithm
%
%    flow = cv.calcOpticalFlowFarneback(prevImg, nextImg)
%
% ## Input
% * __prevImg__ First 8-bit single-channel input image.
% * __nextImg__ Second input image of the same size and the same type as prevImg.
%
% ## Output
% * __flow__ Computed flow image that has the same size as prevImg and single
%         type. flow for (x,y) is stored in the third dimension.
%
% ## Options
% * __InitialFlow__ Initial flow approximation.
% * __PyrScale__ Parameter specifying the image scale (<1) to build pyramids for
%         each image. pyrScale=0.5 means a classical pyramid, where each next
%         layer is twice smaller than the previous one. default 0.5.
% * __Levels__ Number of pyramid layers including the initial image. levels=1
%         means that no extra layers are created and only the original images
%         are used. default 1.
% * __WinSize__ Averaging window size. Larger values increase the algorithm
%         robustness to image noise and give more chances for fast motion
%         detection, but yield more blurred motion field. default 3.
% * __Iterations__ Number of iterations the algorithm does at each pyramid level.
%         default 10.
% * __PolyN__ Size of the pixel neighborhood used to find polynomial expansion in
%         each pixel. Larger values mean that the image will be approximated
%         with smoother surfaces, yielding more robust algorithm and more
%         blurred motion field. Typically, PolyN = 5 or 7. default 5.
% * __PolySigma__ Standard deviation of the Gaussian that is used to smooth
%         derivatives used as a basis for the polynomial expansion. For PolyN =
%         5 , you can set PolySigma=1.1. For PolyN = 7, a good value would be
%         PolySigma = 1.5. default 1.1.
% * __Gaussian__ Use the Gaussian WinSize x WinSize filter instead of a box
%         filter of the same size for optical flow estimation. Usually, this
%         option gives z more accurate flow than with a box filter, at the cost
%         of lower speed. Normally, winsize for a Gaussian window should be set
%         to a larger value to achieve the same level of robustness. default
%         false.
%
% The function finds an optical flow for each prevImg pixel using the
% [Farneback2003] alorithm.
%
% See also cv.calcOpticalFlowPyrLK
%