  Optical Flow algorithms are of high importance for many applications.
Recently, the Flow Field algorithm and its modifications have shown remarkable
results, as they have been evaluated with top accuracy on different data sets.
In our analysis of the algorithm we have found that it produces accurate sparse
matches, but there is room for improvement in the interpolation. Thus, we
propose in this paper FlowFields++, where we combine the accurate matches of
Flow Fields with a robust interpolation. In addition, we propose improved
variational optimization as post-processing. Our new algorithm is evaluated on
the challenging KITTI and MPI Sintel data sets with public top results on both
benchmarks.
