We use a modified version of the Nagel and Enkelmann (1986) classical
method for computation of the optical flow.
We avoid convergence to irrelevant local minima by embedding our method
in a linear scale-space framework and using
a focusing strategy from coarse to fine scales. Our method avoids linearizations
in the optical flow constraint, and it can
recover displacement fields that are far beyond the rypical 1 pixel
limits that are characteristic for many differential
methods for optical flow recovery. We use a robust and efficient implicit
numerical scheme to implement the method.
Ths resulting algorithm depends mainly on the next 4 parameters:
(1)
The initial scale s0. It represents
the standard deviation of the gaussian that we apply to the images in order
to init the focusing strategy.
(2) The decay ratio h. It represents the way
that we choose the different scales in the focusing strategy. That is
si=s0.(h)i.
(3) The isotropy fraction s. It represents the balance in the Nagel operator,
between the isotropic and anisotropic
diffusion.
(4) The regularization parameter a. It represents
the balance between the optical flow constraint and the smoothness
of the flow.
For more details see the paper Reliable Estimation of Optical Flow for Large Displacements
Next we present several experiments to illustrate de algorithm. In you
want to do your own experiments using our algorithm, you
can get here the
Software with the algorithm implemented in different computer arquitectures.