Master data

Title: Video Coding Enhancements for HTTP Adaptive Streaming
Subtitle:
Abstract:

Rapid growth in multimedia streaming traffic over the Internet motivates the research and further investigation of the video coding performance of such services in terms of speed and Quality of Experience (QoE). HTTP Adaptive Streaming (HAS) is today's de-facto standard to deliver clients the highest possible video quality. In HAS, the same video content is encoded at multiple bitrates, resolutions, framerates, and coding formats called representations. This study aims to (i) provide fast and compression-efficient multi-bitrate, multi-resolution representations, (ii) provide fast and compression-efficient multi-codec representations, (iii) improve the encoding efficiency of Video on Demand (VoD) streaming using content-adaptive encoding optimizations, and (iv) provide encoding schemes with optimizations per-title for live streaming applications to decrease the storage or delivery costs or/and increase QoE.

Keywords: Adaptive Streaming, Multi-encoding, Content-adaptive Encoding, Per-title Encoding, Live Streaming
Publication type: Article in Proceedings (Authorship)
Publication date: 10.10.2022 (Print)
Published by: MM'22 Proceedings of the 30th ACM International Conference on Multimedia
MM'22 Proceedings of the 30th ACM International Conference on Multimedia
to publication
 ( ACM Digital Library; )
Title of the series: -
Volume number: -
First publication: Yes
Version: -
Page: pp. 6905 - 6909

Versionen

Keine Version vorhanden
Publication date: 10.10.2022
ISBN:
  • 978-1-4503-9203-7
ISSN: -
Homepage: https://dl.acm.org/doi/10.1145/3503161.3548753
Publication date: 10.10.2022
ISBN (e-book): -
eISSN: -
DOI: http://dx.doi.org/10.1145/3503161.3548753
Homepage: https://dl.acm.org/doi/10.1145/3503161.3548753
Open access
  • Available online (open access)

Authors

Assignment

Organisation Address
Fakultät für Technische Wissenschaften
 
Institut für Informationstechnologie
Universitaetsstr. 65-67
9020 Klagenfurt am Wörthersee
Austria
   martina.steinbacher@aau.at
http://itec.aau.at/
To organisation
Universitaetsstr. 65-67
AT - 9020  Klagenfurt am Wörthersee

Categorisation

Subject areas
  • 1020 - Computer Sciences
Research Cluster No research Research Cluster selected
Peer reviewed
  • Yes
Publication focus
  • Science to Science (Quality indicator: I)
Classification raster of the assigned organisational units:
working groups
  • Multimedia Communication

Cooperations

No partner organisations selected

Articles of the publication

No related publications