"Dual TV L1" Optical Flow Algorithm

The class implements the "Dual TV L1" optical flow algorithm described in [Zach2007] and [Javier2012]. Here are important members of the class that control the algorithm, which you can set after constructing the class instance:

• member double Tau Time step of the numerical scheme.
• member double Lambda 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.
• member double Theta 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.
• member int ScalesNumber Number of scales used to create the pyramid of images.
• member int WarpingsNumber 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.
• member double Epsilon 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.
• member int OuterIterations Stopping criterion iterations number used in the numerical scheme.

References

[Zach2007]:

Christopher Zach, Thomas Pock, and Horst Bischof. "A Duality Based Approach for Realtime TV-L1 Optical Flow". In Pattern Recognition, pages 214-223. Springer, 2007.

[Javier2012]:

Javier Sanchez Perez, Enric Meinhardt-Llopis, and Gabriele Facciolo. "TV-L1 Optical Flow Estimation". 2012.