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AI-based video compression for emerging technologies

Project description

AI mimics human eye for ultra-efficient video compression

The explosion of data and our desire to connect everything, from our ovens to self-driving cars and surgical equipment, to the internet is causing a tremendous flurry of research into how to accommodate all this fast data transmission reliably, securely and with low power consumption. A significant portion of research is directed at technologies to increase bandwidth. The EU-funded AISTREAM project will offer an innovative solution focused on reducing the data – not the actual data going in and coming out but the size during transmission – via AI-supported compression. The team will focus on video, which accounts for a huge volume of the internet traffic, and will demonstrate the technology in a streaming service.

Objective

Deep Render combines the fields of artificial intelligence, statistics and information theory to unlock the fundamental limits of video compression.

The best data compressor known to mankind is the human eye, with compression ratios at least 2,000 times better than anything developed to date. Our Biological Compression technology mimics the neurological processes of the human eye through a non-linear, learning-based approach, creating an innovative class of highly efficient compression algorithms. By building an entirely new foundation for compression, avoiding the limitations of current codecs, our objective is to develop a video compression approach 80% more efficiency than the state-of-the-art.

With 85% of all internet traffic being video data, growing exponentially, bandwidth supply is being used up at an unsustainable rate. Even worse, emerging video technologies such as VR-streaming, Medical and Satellite Imaging, and Autonomous driving are bottlenecked by the unavailability of sufficient bandwidth. Further, the amount of energy used and CO2 generated with online video is now being recognised as a major problem.

If the EU Digital Single Market and economic growth are to be delivered, and Climate Change obligations met, a more efficient compression system is vital to free up bandwidth and reduce energy usage. Our value proposition is simple, by reducing file sizes by 80%, we directly increase the bandwidth supply of the internet by a factor of 5, thus reducing data transport and storage requirements, reducing energy usage and CO2 emissions.

Initially, the end-users of our technology will be content delivery networks, online streaming services and media production organisations. The video encoding market is estimated to be worth €1.5Bn a year. Our collaboration, including TU Wien and Contentflow (end-user), will develop, demonstrate and pilot the codec in a streaming service and begin extending the codec to new high growth, high value and high need markets.

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Programme(s)

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Topic(s)

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Funding Scheme

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IA - Innovation action

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Call for proposal

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(opens in new window) H2020-EIC-FTI-2018-2020

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Coordinator

TECHNISCHE UNIVERSITAET WIEN
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 340 000,00
Address
KARLSPLATZ 13
1040 Wien
Austria

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Region
Ostösterreich Wien Wien
Activity type
Higher or Secondary Education Establishments
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 340 000,00

Participants (2)

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