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.
Z Cam the relatively new Camera company from Shenzhen, China has announced the Z Cam E2 at NAB 2018 MSRP $1,999.00 USD. It is not a direct replacement for their ambitious but half-baked Z E1 m4/3 camera which costs $399. The new camera is a beast specs wise with up to 120fps 4k and full HD 1080p at 240fps. The codecs will be H.264 and H.265 at 10 bit but no RAW support so far which might be acceptable if the codec is clean enough and their promised Log Flat curve preserves the estimated 13.5 stops of dynamic range.
The camera is still being developed for a June 2018 estimated ship date. It lacks a back screen and relies on a Wifi or Gigabit Ethernet link to their dedicated control application. They intend to support iOS devices and or a PC client. No mention of Android support or Mac which should be included in order to maintain the widest compatibility. We feel lacking Android control is a big deal and should be promised in a future update. It is also unclear if the camera will be possible to use by using a touch screen field monitor which probably will not be the case. Using an iPhone or an iPad as the control interface is probably the best use case.
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