NVIDIA has been hard at work on the problem posed by high frame rate interpolation of video data shot on lower fps.  We have had this tech since the late 1990s with the advent of Twixtor and refined over the decades in systems like Twixtor Pro and Adobe’s Optical Flow in After Effects. You are still not getting real temporal detail data since the frames are created by extrapolating velocity and direction vectors plus pixel values between frames to get the result.

We explored this technique in our post on interpolation here and why it is no substitute from a real slow motion camera solution.  NVIDIA’s new method uses machine learning along with 11,000 videos to arrive at a more convincing result. Considering the relatively small sample size we can imagine a future where hundreds of thousands or millions of footage samples are used to generate near flawless interpolation. This technique takes some serious computation and data sets so as of now it is not really ready for the mass market but that could change with the cloud very soon. → Continue Reading Full Post ←