Publikation: Semantic-Aware View Prediction for 360-...
Stammdaten
Titel: | Semantic-Aware View Prediction for 360-Degree Videos at the 5G Edge |
Untertitel: | |
Kurzfassung: | In a 5G testbed, we use 360° video streaming to test, measure, and demonstrate the 5G infrastructure, including the capabilities and challenges of edge computing support. Specifically, we use the SEAWARE (Semantic-Aware View Prediction) software system, originally described in [1], at the edge of the 5G network to support a 360° video player (handling tiled videos) by view prediction. Originally, SEAWARE performs semantic analysis of a 360° video on the media server, by extracting, e.g., important objects and events. This video semantic information is encoded in specific data structures and shared with the client in a DASH streaming framework. Making use of these data structures, the client/player can perform view prediction without in-depth, computationally expensive semantic video analysis. In this paper, the SEAWARE system was ported and adapted to run (partially) on the edge where it can be used to predict views and prefetch predicted segments/tiles in high quality in order to have them available close to the client when requested. The paper gives an overview of the 5G testbed, the overall architecture, and the implementation of SEAWARE at the edge server. Since an important goal of this work is to achieve low motion-to-glass latencies, we developed and describe "tile postloading", a technique that allows non-predicted tiles to be fetched in high quality into a segment already available in the player buffer. The performance of 360° tiled video playback on the 5G infrastructure is evaluated and presented. Current limitations of the 5G network in use and some challenges of DASH-based streaming and of edge-assisted viewport prediction under "real-world" constraints are pointed out; further, the performance benefits of tile postloading are disclosed. |
Schlagworte: | Tile-based 360° video streaming, viewport prediction, tile postloading, 5G networks, edge computing |
Publikationstyp: | Beitrag in Proceedings (Autorenschaft) |
Erscheinungsdatum: | 23.01.2023 (Online) |
Erschienen in: |
ISM'22 Proceedings of the IEEE International Symposium on Multimedia (ISM 2022)
ISM'22 Proceedings of the IEEE International Symposium on Multimedia (ISM 2022)
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IEEE Xplore Digital Library;
)
zur Publikation |
Titel der Serie: | - |
Bandnummer: | - |
Erstveröffentlichung: | Ja |
Version: | - |
Seite: | S. 121 - 128 |
Versionen
Keine Version vorhanden |
Erscheinungsdatum: | 12.2022 |
ISBN: |
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ISSN: | - |
Homepage: | https://ieeexplore.ieee.org/document/10019680 |
Erscheinungsdatum: | 23.01.2023 |
ISBN (e-book): | - |
eISSN: | - |
DOI: | http://dx.doi.org/10.1109/ism55400.2022.00025 |
Homepage: | https://ieeexplore.ieee.org/document/10019680 |
Open Access |
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Wibi-relevante Version |
AutorInnen
Shivi Vats (intern) |
Jounsup Park (extern) |
Klara Nahrstedt (extern) |
Michael Zink (extern) |
Ramesh Sitaraman (extern) |
Hermann Hellwagner (intern) |
Zuordnung
Organisation | Adresse | ||||
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Fakultät für Technische Wissenschaften
Institut für Informationstechnologie
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AT - 9020 Klagenfurt am Wörthersee |
Kategorisierung
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Forschungscluster | Kein Forschungscluster ausgewählt |
Peer Reviewed |
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Publikationsfokus |
Klassifikationsraster der zugeordneten Organisationseinheiten:
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Kooperationen
Organisation | Adresse | ||
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California Baptist University
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US - CA 92504 Riverside |
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University of Illinois
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US
Chicago |
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University of Massachusetts Amherst
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US
- MA 01003
Amherst |
Forschungsaktivitäten
(Achtung: Externe Aktivitäten werden im Suchergebnis nicht mitangezeigt)
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Publikationen: | Keine verknüpften Publikationen vorhanden |
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