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SMPTE Meetings and Conferences ( October 2019)
[ACTIVE]

How AI Technology is Dramatically Improving Video Compression for Broadcast and OTT Content Delivery

Metadata

Publisher
SMPTE — White Plains, NY, USA
Doc Type
Conference Paper
Content Type
Original Research
Volume
2019, No. 10, pp. 1–14
Abstract
Video compression for broadcast TV services started more than 20 years ago. Since then, there has been a major codec standard created about every 10 years, with MPEG-2 released around 1995, AVC in 2005 and HEVC in 2015. Over time, several key improvements such as dual-pass encoding, statistical multiplexing and software migration were made to compression technology in order to boost performance. Tuning the algorithms and the algorithmic tools also allowed significant improvements to be made. — Now a new and disruptive technology — Artificial Intelligence (AI) — is driving the next frontier of video compression enhancements with the promise of faster advancements. AI is being used to improve several key areas: to achieve better video quality (VQ) at a given bit rate, or lower bit rate at the same VQ. Advances are also being made in other directions, like higher density to where the same VQ/bitrate efficiency will use less computing resources, and in providing better quality of experiences (QoE). — This paper will present three examples of AI applied to video encoding to optimize broadcast and OTT content delivery: Dynamic Encoding Style (DES) for a better VQ /bitrate trade-off, Dynamic Resolution Encoding (DRE) for better QoE and density, and Dynamic Frame rate Encoding (DFE) also for improved density and QoE. — In addition, the paper will explore the operational and end-user benefits enabled by AI and machine learning. Additionally, it will provide measurement for the applications that are presented and address the possible future evolutions of AI for video compression.
Publication Date
2019-10-21
DOI
10.5594/M001868
Link
https://doi.org/10.5594/M001868
Author(s)
Jean-Louis DiascornHarmonic, San Jose, California, USA
Keyword(s)
Artificial Intelligence, Machine Learning, Video, Compression, Density, CPU, Latency, Television, Live Production
Copyright
© 2019 Society of Motion Picture and Television Engineers, Inc.

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Jean-Louis Diascorn; How AI Technology is Dramatically Improving Video Compression for Broadcast and OTT Content Delivery, SMPTE Meetings and Conferences ( October 2019); SMPTE, 2019. Available at https://doi.org/10.5594/M001868
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Jean-Louis Diascorn; How AI Technology is Dramatically Improving Video Compression for Broadcast and OTT Content Delivery, SMPTE Meetings and Conferences ( October 2019); SMPTE, 2019. Available at https://doi.org/10.5594/M001868

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Jean-Louis Diascorn; How AI Technology is Dramatically Improving Video Compression for Broadcast and OTT Content Delivery, SMPTE Meetings and Conferences ( October 2019); SMPTE, 2019. Available at https://doi.org/10.5594/M001868
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<span class="citation">Jean-Louis Diascorn; <cite>How AI Technology is Dramatically Improving Video Compression for Broadcast and OTT Content Delivery</cite>, SMPTE Meetings and Conferences ( October 2019); SMPTE, 2019. Available at <a href="https://doi.org/10.5594/M001868" target="_blank" rel="noopener">https://doi.org/10.5594/M001868</a></span>

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Preview:
Jean-Louis Diascorn; How AI Technology is Dramatically Improving Video Compression for Broadcast and OTT Content Delivery, SMPTE Meetings and Conferences ( October 2019); SMPTE, 2019
doi: 10.5594/M001868
url: https://doi.org/10.5594/M001868
Snippet:
<li>
Jean-Louis Diascorn; <cite id="bib-10-5594-m001868">How AI Technology is Dramatically Improving Video Compression for Broadcast and OTT Content Delivery</cite>, SMPTE Meetings and Conferences ( October 2019); SMPTE, 2019
<span class="doi">10.5594/M001868</span>
</li>