Abstract

After the emergence of video streaming services, more creative and diverse multimedia content has become available, and now the capability of streaming 360-degree videos will open a new era of multimedia experiences. However, streaming these videos requires larger bandwidth and less latency than what is found in conventional video streaming systems. Rate adaptation of tiled videos and view prediction techniques are used to solve this problem. In this paper, we introduce the Navigation Graph, which models viewing behaviors in the temporal (segments) and the spatial (tiles) domains to perform the rate adaptation of tiled media associated with the view prediction. The Navigation Graph allows clients to perform view prediction more easily by sharing the viewing model in the same way in which media description information is shared in DASH. It is also useful for encoding the trajectory information in the media description file, which could also allow for more efficient navigation of 360-degree videos. This paper provides information about the creation of the Navigation Graph and its uses. The performance evaluation shows that the Navigation Graph based view prediction and rate adaptation outperform other existing tiled media streaming solutions. Navigation Graph is not limited to 360-degree video streaming applications, but it can also be applied to other tiled media streaming systems, such as volumetric media streaming for augmented reality applications.

Original languageEnglish (US)
Title of host publicationMM 2019 - Proceedings of the 27th ACM International Conference on Multimedia
PublisherAssociation for Computing Machinery, Inc
Pages447-455
Number of pages9
ISBN (Electronic)9781450368896
DOIs
StatePublished - Oct 15 2019
Event27th ACM International Conference on Multimedia, MM 2019 - Nice, France
Duration: Oct 21 2019Oct 25 2019

Publication series

NameMM 2019 - Proceedings of the 27th ACM International Conference on Multimedia

Conference

Conference27th ACM International Conference on Multimedia, MM 2019
CountryFrance
CityNice
Period10/21/1910/25/19

Keywords

  • Rate adaptation
  • Tiled media streaming
  • View prediction

ASJC Scopus subject areas

  • Computer Science(all)
  • Media Technology

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