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.
Bibliographic Reference(s)
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- A. Agrawal, J. Gans, A. Goldfarb, “Prediction Machines: The Simple Economics of Artificial Intelligence,” Harvard Business School Press, April 2018. EXTERNAL
- “Per-Title Encode Optimization,” Netflix Tech Blog, Dec. 2015, https://medium.com/netflix-techblog/per-title-encode-optimization-7e99442b62a2. EXTERNAL
- Press release on DES (to be updated) EXTERNAL
- Q. Huang, S. Y. Jeong, S. Yang, D. Zhang, S. Hu, H. Y. Kim, J. S. Choi, and C.-C. J. Kuo, “Perceptual Quality Driven Frame-Rate Selection (pqd- EXTERNAL
- A. V. Katsenou, D. Ma, and D. R. Bull, “Perceptually Aligned Frame Rate Selection Using Spatio Temporal Features,” Picture Coding Symposium (PCS), 2018. IEEE, 2018, pp. 1–5. EXTERNAL
- “Dynamic Frame Rate” paper (exact reference to be updated), IEEE Transactions on Broadcasting 2019. Need to cite authors EXTERNAL
- J.L. Diascorn, “AI Technology is Changing the Future of Video Compression,” NAB 2019 technology paper, Broadcast Engineering and Information Technology Conference, April 2019. EXTERNAL
- M. Gary, “DeepMind's Losses and the Future of Artificial Intelligence,” Wired, September 2019, https://www.wired.com/story/deepminds-losses-future-artificial-intelligence/ EXTERNAL
- R. Cyrus, “Bias in AI: A Problem Recognized but Still Unresolved,” Tech Crunch, July 2019, https://techcrunch.com/2019/07/25/bias-in-ai-a-problem-recognized-but-still-unresolved/ EXTERNAL
- Y. Liu, et al., “Artificial Intelligence-Based Breast Cancer Nodal Metastasis Detection,” Arch Pathol Lab Med., October 2018. EXTERNAL
- reference to VVC with AI (to be updated). EXTERNAL
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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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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
doi: 10.5594/M001868
url: https://doi.org/10.5594/M001868
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<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>