Master data

Title: Perceptually-Aware Per-Title Encoding for Adaptive Video Streaming
Subtitle:
Abstract:

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.

Keywords:
Publication type: Article in Proceedings (Authorship)
Publication date: 18.07.2022 (Print)
Published by: ICME '22 Proceedings of the IEEE International Conference on Multimedia and Expo
ICME '22 Proceedings of the IEEE International Conference on Multimedia and Expo
to publication
 ( IEEE; )
Title of the series: -
Volume number: -
First publication: Yes
Version: -
Page: pp. 1 - 6

Versionen

Keine Version vorhanden
Publication date: 18.07.2022
ISBN: -
ISSN: -
Homepage: https://www.computer.org/csdl/proceedings-article/icme/2022/09859744/1G9EBLa3Dz2
Publication date: 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
  • Available online (not open access)

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