Stammdaten

Titel: Towards Optimal Multirate Encoding for HTTP Adaptive Streaming
Untertitel:
Kurzfassung:

HTTP Adaptive Streaming (HAS) enables high quality stream-ing of video contents. In HAS, videos are divided into short intervalscalled segments, and each segment is encoded at various quality/bitratesto adapt to the available bandwidth. Multiple encodings of the same con-tent imposes high cost for video content providers. To reduce the time-complexity of encoding multiple representations, state-of-the-art methods typically encode the highest quality representation first and reusethe information gathered during its encoding to accelerate the encodingof the remaining representations. As encoding the highest quality rep-resentation requires the highest time-complexity compared to the lowerquality representations, it would be a bottleneck in parallel encoding scenarios and the overall time-complexity will be limited to the time-complexity of the highest quality representation. In this paper and toaddress this problem, we consider all representations from the highestto the lowest quality representation as a potential, single reference toaccelerate the encoding of the other, dependent representations. We for-mulate a set of encoding modes and assess their performance in terms ofBD-Rate and time-complexity, using both VMAF and PSNR as objec-tive metrics. Experimental results show that encoding a middle qualityrepresentation as a reference, can significantly reduce the maximum en-coding complexity and hence it is an efficient way of encoding multiplerepresentations in parallel. Based on this fact, a fast multirate encodingmethod is proposed which utilizes depth and prediction mode of a middle quality representation to accelerate the encoding of the dependentrepresentations.

Schlagworte: HEVC; Video Encoding; Multirate Encoding; DASH
Publikationstyp: Beitrag in Proceedings (Autorenschaft)
Erscheinungsdatum: 21.01.2021 (Online)
Erschienen in: MMM 21' Proceedings of the 27th Internationl Conference on Multimedia Modeling (MMM 2021)
MMM 21' Proceedings of the 27th Internationl Conference on Multimedia Modeling (MMM 2021)
zur Publikation
 ( Springer; J. Lokoc, T. Skopal , K. Schöffmann, V. Mezaris, X. Li, S. Vrochidis, I. Patras )
Titel der Serie: Lecture Notes in Computer Science
Bandnummer: 12572
Erstveröffentlichung: Ja
Version: -
Seite: S. 469 - 480

Versionen

Keine Version vorhanden
Erscheinungsdatum: 21.01.2021
ISBN (e-book):
  • 978-3-030-67831-9
  • 978-3-030-67832-6
eISSN: -
DOI: http://dx.doi.org/10.1007/978-3-030-67832-6_38
Homepage: https://link.springer.com/chapter/10.1007/978-3-030-67832-6_38
Open Access
  • Online verfügbar (nicht Open Access)

Zuordnung

Organisation Adresse
Fakultät für Technische Wissenschaften
 
Institut für Informationstechnologie
Universitaetsstr. 65-67
9020 Klagenfurt am Wörthersee
Österreich
   martina.steinbacher@aau.at
http://itec.aau.at/
zur Organisation
Universitaetsstr. 65-67
AT - 9020  Klagenfurt am Wörthersee

Kategorisierung

Sachgebiete
  • 1020 - Informatik
Forschungscluster Kein Forschungscluster ausgewählt
Peer Reviewed
  • Ja
Publikationsfokus
  • Science to Science (Qualitätsindikator: II)
Klassifikationsraster der zugeordneten Organisationseinheiten:
Arbeitsgruppen
  • Multimedia Communication

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Beiträge der Publikation

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