Stammdaten

Titel: Dynamic Adaptive Point Cloud Streaming
Untertitel:
Kurzfassung:

High-quality point clouds have recently gained interest as an emerging form of representing immersive 3D graphics. Unfortunately, these 3D media are bulky and severely bandwidth intensive, which makes it difficult for streaming to resource-limited and mobile devices. This has called researchers to propose efficient and adaptive approaches for streaming of high-quality point clouds.

In this paper, we run a pilot study towards dynamic adaptive point cloud streaming, and extend the concept of dynamic adaptive streaming over HTTP (DASH) towards DASH-PC, a dynamic adaptive bandwidth-efficient and view-aware point cloud streaming system. DASH-PC can tackle the huge bandwidth demands of dense point cloud streaming while at the same time can semantically link to human visual acuity to maintain high visual quality when needed. In order to describe the various quality representations, we propose multiple thinning approaches to spatially sub-sample point clouds in the 3D space, and design a DASH Media Presentation Description manifest speci.c for point cloud streaming. Our initial evaluations show that we can achieve signi.cant bandwidth and performance improvement on dense point cloud streaming with minor negative quality impacts compared to the baseline scenario when no adaptations is applied.

Schlagworte:
Publikationstyp: Beitrag in Sammelwerk (Autorenschaft)
Art der Veröffentlichung Printversion
Erschienen in: PV '18 Proceedings of the 23rd Packet Video Workshop
PV '18 Proceedings of the 23rd Packet Video Workshop
zur Publikation
 ( ACM Press; )
Erscheinungsdatum: 06.2018
Titel der Serie: -
Bandnummer: -
Erstveröffentlichung: Ja
Seite: S. 25 - 30

Identifikatoren

ISBN:
  • 978-1-4503-5773-9
ISSN: -
DOI: http://dx.doi.org/10.1145/3210424.3210429
AC-Nummer: -
Homepage: https://dl.acm.org/citation.cfm?id=3210429
Open Access
  • Online verfügbar (nicht Open Access)

AutorInnen

Zuordnung

Organisation Adresse
Fakultät für Technische Wissenschaften
 
Institut für Informationstechnologie
Universitaetsstr. 65-67
9020  Klagenfurt am Wörthersee
Österreich
  -3699
   martina.steinbacher@uni-klu.ac.at
http://itec.aau.at/
zur Organisation
Universitaetsstr. 65-67
AT - 9020  Klagenfurt am Wörthersee

Kategorisierung

Sachgebiete
  • 1020 - Informatik
Forschungscluster Kein Forschungscluster ausgewählt
Peer Reviewed
  • Ja
Publikationsfokus
  • Science to Science (Qualitätsindikator: II)
Klassifikationsraster der zugeordneten Organisationseinheiten:
Arbeitsgruppen
  • Multimedia Communication

Kooperationen

Organisation Adresse
University of Illinois
Chicago
Vereinigte St. v. Amerika
US  Chicago

Beiträge der Publikation

Keine verknüpften Publikationen vorhanden