Publication: A Scalable Video Coding Dataset and Too...
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. |
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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
(
ACM Press;
W. Tsang Ooi
)
to publication |
Title of the series: | - |
Volume number: | - |
First publication: | Yes |
Version: | - |
Page: | pp. 213 - 218 |
Versionen
Keine Version vorhanden |
Publication date: | 03.2015 |
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eISSN: | - |
DOI: | http://dx.doi.org/10.1145/2713168.2713193 |
Homepage: | http://dl.acm.org/citation.cfm?id=2713193 |
Open access |
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Assignment
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Fakultät für Technische Wissenschaften
Institut für Informationstechnologie
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AT - 9020 Klagenfurt am Wörthersee |
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Research Cluster | No research Research Cluster selected |
Peer reviewed |
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