Current per-title encoding schemes encode the same video content at various bitrates and spatial resolutions to find optimal bitrate-resolution pairs (known as bitrate ladder) for each video content in Video on Demand (VoD) applications. But in live streaming applications, a fixed bitrate ladder is used for simplicity and efficiency to avoid the additional latency to find the optimized bitrate-resolution pairs for every video content. However, an optimized bitrate ladder may result in (i) decreased storage or network resources or/and (ii) increased Quality of Experience (QoE). In this paper, a fast and efficient per-title encoding scheme (Live-PSTR) is proposed tailor-made for live Ultra High Definition (UHD) High Framerate (HFR) streaming. It includes a pre-processing step in which Discrete Cosine Transform (DCT)-energy-based low-complexity spatial and temporal features are used to determine the complexity of each video segment, based on which the optimized encoding resolution and framerate for streaming at every target bitrate is determined. Experimental results show that, on average, Live-PSTR yields bitrate savings of 9.46% and 11.99% to maintain the same PSNR and VMAF scores, respectively compared to the HTTP Live Streaming (HLS) bitrate ladder.

1. Live-PSTR: Live Per-title Encoding for
Ultra HD Adaptive Streaming
Vignesh V Menon (AAU), Hadi Amirpour (AAU), Christian Feldmann (Bitmovin),
Adithyan Ilangovan (Bitmovin), Martin Smole (Bitmovin), Mohammad Ghanbari (AAU),
and Christian Timmerer (AAU, Director at CD Lab ATHENA)
April 24, 2022
2022 NAB Broadcast Engineering and Information Technology (BEIT) Conference
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2. Presenter
Christian Timmerer
Assoc.-Prof at
Alpen-Adria-Universität Klagenfurt
Director CD Lab ATHENA
CIO | Head of Research and
Standardization at Bitmovin
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2003: MSc CS (Dipl.-Ing.)
2006: PhD CS (Dr.-techn.)
2013: Co-founded Bitmovin
2014: Habilitation (Priv.-Doz.) & Assoc. Prof.
2016: Dep. Director @ ITEC/AAU
2019: Director @ ATHENA
Web: http://timmerer.com/, @timse7
72nd (Bitmovin) and 73rd (MPEG-DASH) Annual
Technology & Engineering Emmy® Awards

3. Video streaming is dominating today’s Internet traffic
● Jan. 2022: 53.7%; YouTube is the undisputed king with
16.3% followed by Netflix with 10.6% (downlink traffic)*
● Cisco VNI: live video will increase 15-fold and reach 17% of
Internet video traffic**
● Increase of spatial (UHD) and temporal resolution (HFR)
Motivation
Sources: * Sandvine Global
Internet Phenomena (May 2020).
** Cisco Visual Networking Index
(VNI), Complete Forecast
Update, 2017–2022 (Feb. 2019)
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4. HTTP Adaptive Streaming (HAS)
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Client
A. Bentaleb, B. Taani, A. C. Begen, C. Timmerer and R. Zimmermann, "A Survey on Bitrate
Adaptation Schemes for Streaming Media Over HTTP," in IEEE Communications
Surveys & Tutorials, vol. 21, no. 1, pp. 562-585, Firstquarter 2019. doi:
10.1109/COMST.2018.2862938

5. Live streaming
● Static bitrate ladder
Pre-defined bitrate/resolution pairs for all contents
● Per-title encoding
Optimize bitrate ladder based on the content
● UHD / HFR content
Increase of spatial and temporal resolutions
● Live-PSTR
Resolution & framerate prediction algorithm
based on the content complexity (E, h)
Problem Statement / Basic Idea
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6. Spatial (E) / Temporal (h) Content Characteristics
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Video Complexity Analyzer (VCA)
https://multimediacommunication.blogspot.com/2022/03/video-complexity-analyzer-vca-v10.html
V. V Menon, C. Feldmann, H. Amirpour, M. Ghanbari, C. Timmerer, “VCA: Video Complexity
Analyzer”, accepted for publication in ACM MMSys 2022, Athlone, Ireland, June 2022.

7. Live-PSTR: Scheme
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VCA: Video Complexity Analyzer (to extract/calculate E/h metrics)
Github: https://github.com/cd-athena/VCA
Documentation: https://cd-athena.github.io/VCA/

8. Live-PSTR: Example Bitrate Ladder
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9. Live-PSTR: Example Frames (1)
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10. Live-PSTR: Example Frames (2)
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11. Live-PSTR vs. Fixed Bitrate Ladder (1)
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12. Live-PSTR vs. Fixed Bitrate Ladder (2)
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13. Live-PSTR
● Online per-title encoding scheme with spatial and temporal resolutions
Target application: live streaming of UHD HFR videos
● Live-PSTR features
Convex-hull prediction algorithm that predicts the optimized resolution and
framerate for a given target bitrate for each segment
● How is it done?
DCT-energy-based features to determine the segments’
spatial (E) and temporal (h) complexities; fast and effective!
● Live-PSTR experimental results
9.46% less bits (PSNR); 11.99% less bits (VMAF) compared to fixed bitrate ladder
Conclusions
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14. Thank you for your attention
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https://athena.itec.aau.at/

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