Efficient viewport prediction and tiling schemes for 360 degree video streaming

Jayasingam Adhuran; Maria G. Martini

doi:10.1145/3625468.3653425

Efficient viewport prediction and tiling schemes for 360 degree video streaming

Jayasingam Adhuran
, Maria G. Martini

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

61 Downloads (Pure)

Abstract

360-degree video streaming for VR visualisation is characterised by large transmission data volume and stringent interactive latency demands; hence guaranteeing suitable transmission quality, while meeting the existing constraints, is highly challenging. This paper addresses the relevant grand challenge presented at MMSys 2024 on 360-degree video on-demand streaming, aiming at designing and implementing a 360-degree video on-demand streaming solution using the open-source evaluation platform E3PO. The proposed solution incorporates several strategies including viewport prediction, tiling, encoding tile selection for streaming and upsampling.

Original language	English
Title of host publication	MMSys '24
Subtitle of host publication	proceedings of the 15th ACM Multimedia Systems Conference
Place of Publication	New York, U.S.
Publisher	Association for Computing Machinery
ISBN (Print)	9798400704123
DOIs	https://doi.org/10.1145/3625468.3653425
Publication status	Published - 16 Apr 2024
Event	15th ACM Multimedia Systems Conference (MMSys 2024) - Bari, Italy Duration: 15 Apr 2024 → 18 Apr 2024

Conference

Conference	15th ACM Multimedia Systems Conference (MMSys 2024)
Period	15/04/24 → 18/04/24

Bibliographical note

Organising Body: Association for Computing Machinery

Keywords

Computer science and informatics

Access to Document

10.1145/3625468.3653425

Martini-M-54653-AAMAccepted author manuscript, 11.5 MBLicence: Unspecified

Cite this

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title = "Efficient viewport prediction and tiling schemes for 360 degree video streaming",

abstract = "360-degree video streaming for VR visualisation is characterised by large transmission data volume and stringent interactive latency demands; hence guaranteeing suitable transmission quality, while meeting the existing constraints, is highly challenging. This paper addresses the relevant grand challenge presented at MMSys 2024 on 360-degree video on-demand streaming, aiming at designing and implementing a 360-degree video on-demand streaming solution using the open-source evaluation platform E3PO. The proposed solution incorporates several strategies including viewport prediction, tiling, encoding tile selection for streaming and upsampling. ",

keywords = "Computer science and informatics",

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doi = "10.1145/3625468.3653425",

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AU - Adhuran, Jayasingam

AU - Martini, Maria G.

N1 - Organising Body: Association for Computing Machinery

PY - 2024/4/16

Y1 - 2024/4/16

N2 - 360-degree video streaming for VR visualisation is characterised by large transmission data volume and stringent interactive latency demands; hence guaranteeing suitable transmission quality, while meeting the existing constraints, is highly challenging. This paper addresses the relevant grand challenge presented at MMSys 2024 on 360-degree video on-demand streaming, aiming at designing and implementing a 360-degree video on-demand streaming solution using the open-source evaluation platform E3PO. The proposed solution incorporates several strategies including viewport prediction, tiling, encoding tile selection for streaming and upsampling.

AB - 360-degree video streaming for VR visualisation is characterised by large transmission data volume and stringent interactive latency demands; hence guaranteeing suitable transmission quality, while meeting the existing constraints, is highly challenging. This paper addresses the relevant grand challenge presented at MMSys 2024 on 360-degree video on-demand streaming, aiming at designing and implementing a 360-degree video on-demand streaming solution using the open-source evaluation platform E3PO. The proposed solution incorporates several strategies including viewport prediction, tiling, encoding tile selection for streaming and upsampling.

KW - Computer science and informatics

U2 - 10.1145/3625468.3653425

DO - 10.1145/3625468.3653425

M3 - Conference contribution

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BT - MMSys '24

PB - Association for Computing Machinery

CY - New York, U.S.

T2 - 15th ACM Multimedia Systems Conference (MMSys 2024)

Y2 - 15 April 2024 through 18 April 2024

ER -

Efficient viewport prediction and tiling schemes for 360 degree video streaming

Abstract

Conference

Bibliographical note

Keywords

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Cite this