Publikation: Perceptually-Aware Per-Title Encoding f...
Stammdaten
Titel: | Perceptually-Aware Per-Title Encoding for Adaptive Video Streaming |
Untertitel: | |
Kurzfassung: | In live streaming applications, a fixed set of bitrate-resolution pairs (known as bitrate ladder) is used for simplicity and efficiency to avoid the additional encoding run-time required to find optimum resolution-bitrate pairs for every video content. However, an optimized bitrate ladder may result in (i) decreased storage or delivery costs or/and (ii) increased Quality of Experience (QoE). This paper introduces a perceptually-aware per-title encoding (PPTE) scheme for video streaming applications. In this scheme, optimized bitrate-resolution pairs are predicted online based on Just Noticeable Difference (JND) in quality perception to avoid adding perceptually similar representations in the bitrate ladder. To this end, Discrete Cosine Transform (DCT)-energy-based low-complexity spatial and temporal features for each video segment are used. Experimental results show that, on average, PPTE yields bitrate savings of 16.47% and 27.02% to maintain the same PSNR and VMAF, respectively, compared to the reference HTTP Live Streaming (HLS) bitrate ladder without any noticeable additional latency in streaming accompanied by a 30.69% cumulative decrease in storage space for various representations. |
Schlagworte: |
Publikationstyp: | Beitrag in Proceedings (Autorenschaft) |
Erscheinungsdatum: | 18.07.2022 (Print) |
Erschienen in: |
ICME '22 Proceedings of the IEEE International Conference on Multimedia and Expo
ICME '22 Proceedings of the IEEE International Conference on Multimedia and Expo
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IEEE;
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zur Publikation |
Titel der Serie: | - |
Bandnummer: | - |
Erstveröffentlichung: | Ja |
Version: | - |
Seite: | S. 1 - 6 |
Versionen
Keine Version vorhanden |
Erscheinungsdatum: | 18.07.2022 |
ISBN: | - |
ISSN: | - |
Homepage: | https://www.computer.org/csdl/proceedings-article/icme/2022/09859744/1G9EBLa3Dz2 |
Erscheinungsdatum: | 18.07.2022 |
ISBN (e-book): | - |
eISSN: | - |
DOI: | http://dx.doi.org/10.1109/icme52920.2022.9859744 |
Homepage: | https://www.computer.org/csdl/proceedings-article/icme/2022/09859744/1G9EBLa3Dz2 |
Open Access |
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AutorInnen
Vignesh Menon (intern) |
Hadi Amirpourazarian (intern) |
Mohammad Ghanbari (intern) |
Christian Timmerer (intern) |
Zuordnung
Organisation | Adresse | ||||
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Fakultät für Technische Wissenschaften
Institut für Informationstechnologie
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AT - 9020 Klagenfurt am Wörthersee |
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