Master data

Title: A Scalable Video Coding Dataset and Toolchain for Dynamic Adaptive Streaming over HTTP
Subtitle:
Abstract:

With video streaming becoming more and more popular, the number of devices that are capable of streaming videos over the Internet is growing. This leads to a heterogeneous device landscape with varying demands. Dynamic Adaptive Streaming over HTTP (DASH) offers an elegant solution to these demands. Smart adaptation logics are able to adjust the clients' streaming quality according to several (local) parameters. Recent research indicated benefits of blending Scalable Video Coding (SVC) with DASH, especially considering Future Internet architectures. However, except for a DASH dataset with a single SVC encoded video, no other datasets are publicly available. The contribution of this paper is two-fold. First, a DASH/SVC dataset, containing multiple videos at varying bitrates and spatial resolutions including 1080p, is presented. Second, a toolchain for multiplexing SVC encoded videos is provided, therefore making our results reproducible and allowing researchers to generate their own datasets.

Keywords:
Publication type: Article in compilation (Authorship)
Publication date: 03.2015 (Online)
Published by: MMSys '15 Proceedings of the 6th ACM Multimedia Systems Conference
MMSys '15 Proceedings of the 6th ACM Multimedia Systems Conference
to publication
 ( ACM Press; W. Tsang Ooi )
Title of the series: -
Volume number: -
First publication: Yes
Version: -
Page: pp. 213 - 218

Versionen

Keine Version vorhanden
Publication date: 03.2015
ISBN (e-book):
  • 978-1-4503-3351-1
eISSN: -
DOI: http://dx.doi.org/10.1145/2713168.2713193
Homepage: http://dl.acm.org/citation.cfm?id=2713193
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: II)
Classification raster of the assigned organisational units:
working groups
  • Multimedia Communication

Cooperations

No partner organisations selected

Articles of the publication

No related publications