Video Gorillas’ Groundbreaking Bigfoot Frame Compare Solution Now Commercially Available

LOS ANGELES–([1])–Video Gorillas, a developer of state-of-the-art media technology
incorporating machine learning, neural networks, visual analysis, object
recognition, and live streaming, announced today the commercially
available version of its Bigfoot Frame Compare product, which is set to
redefine the way film, television, and post-production companies manage
assets, finishing, and remastering and preservation projects.

Bigfoot is a scalable, lightweight proprietary technology that leverages
Video Gorillas’ patented computer vision/visual analysis, Frequency
Domain Descriptor (FDD), and machine learning technology. It is designed
to automate the manual-labor intensive conform process (which matches an
original frame of film to the final edited work) and the compare process
(which compares unique or common frames between different film cuts) by
finding like “interest points” common across a series of images or
frames of film.

Existing interest point matching methods require enormous computer
processing speeds and large index sizes, making them difficult to scale.
Similarly, pixel-matching solutions have limitations that make them
impractical for all but very specific, uncommon film and television
projects. Thus conform is traditionally a bottleneck in post-production
because “eyematching” has been the only consistently reliable solution –
a human being in an edit suite matching frames by eye. This effort
requires highly skilled labor, expensive facilities and data storage,
and the work is time-consuming, inefficient, and not creative. For
example, a one hour, VFX-heavy television episode with 1.3 million
frames (approximately 80,000 feet of film) and 89 scans with a duration
of 14:56:20 (around 16TB) would ordinarily take 8-10 days to conform. By
contrast, Bigfoot is a scalable, automated, lightweight solution capable
of completing the same task in 10-12 hours.

“We worked with a select group of film and television customers on
hundreds of projects for several months to prove the Bigfoot concept and
achieved exceptional results, and we’re thrilled to make Bigfoot widely
available to the Media & Entertainment industry,” said Video Gorillas
CEO Jason Brahms. “Bigfoot enables a previously unimaginable level of
speed, efficiency, and transparency in remastering, localization and
restoration workflows, reducing the time to market for content owners,
unlocking additional value in film and television libraries, and
supporting ongoing preservation efforts.”

Bigfoot Frame Compare is capable of performing complex tasks at high
speeds, such as differential analysis of frames that are unique, common,
or have shifted or moved between two versions or cuts of a film or TV
show, as well as determining whether the common frames are identical.
Bigfoot can auto-conform restoration or remastering projects by
comparing the frames from a reference picture to those from film scans,
and reconstruct the timeline using the sequences of frames that have the
most points in common. Additional conform projects Bigfoot supports

  • A/B reels to reference picture conform
  • Matching VFX plates or green screen to reference picture
  • Trailer reconstruction from scans
  • News reel reconstruction
  • Matching stock footage

Bigfoot, which as of today is commercially available for companies
across the Media & Entertainment industry, combines state-of-the-art
machine learning technology and delivers it all inside Docker
containers, making it the easiest way for developers to build and deploy
artificial intelligence into their applications both in the cloud and on
premises. It also enables front-end validation UIs that work in a web

About Video Gorillas

Video Gorillas is a media-focused product and services company that
develops state-of-the-art video technology incorporating machine
learning, neural networks, visual analysis, object recognition, and live
streaming. The company is headquartered in Los Angeles with engineering
based in Kiev. For more information visit:[2].

Copyright © 2018 Video Gorillas LLC. All rights reserved. Video
Gorillas LLC, its subsidiaries, and their respective taglines are either
trademarks or registered trademarks of Video Gorillas LLC or its
subsidiaries in the United States and/or other countries. All other
trademarks used are owned by their respective owners.


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