Elevating Your Streaming Experience with Just Noticeable Difference (JND)-based Encoding

Jingwen Zhu; H. Amirpour; Vignesh V Menon; Raimund Schatz; Patrick Le Callet

doi:10.1145/3588444.3591025

Elevating Your Streaming Experience with Just Noticeable Difference (JND)-based Encoding

Jingwen Zhu
, H. Amirpour
, Vignesh V Menon
, Raimund Schatz
, Patrick Le Callet

Experience Contexts & Tools

Université de Nantes
University of Klagenfurt
Institute of Social Ecology, Alpen-Adria-Universita¨t Klagenfurt|Wien|Graz

Publikation: Beitrag in Buch oder Tagungsband › Vortrag mit Beitrag in Tagungsband › Begutachtung

Abstract

With the growing number of video streaming applications, intelligent video streaming has become increasingly important. By considering JND, video delivery can be improved by avoiding the selection of encodings with similar quality for a bitrate ladder. In this paper, we present an overview of the existing methods for modeling and predicting JND in the context of video streaming applications.

Originalsprache	Englisch
Titel	Proceedings of the 2nd Mile-High Video Conference
Erscheinungsort	New York, NY, USA
Seiten	128-129
Seitenumfang	2
DOIs	https://doi.org/10.1145/3588444.3591025
Publikationsstatus	Veröffentlicht - 16 Juni 2023
Veranstaltung	ACM MILE-HIGH VIDEO 2023 - Grand Hyatt Denver, Denver, USA/Vereinigte Staaten Dauer: 7 Mai 2023 → 10 Mai 2023 https://www.mile-high.video/

Publikationsreihe

Name	MHV '23
Herausgeber (Verlag)	Association for Computing Machinery

Konferenz

Konferenz	ACM MILE-HIGH VIDEO 2023
Kurztitel	mhv 2023
Land/Gebiet	USA/Vereinigte Staaten
Stadt	Denver
Zeitraum	7/05/23 → 10/05/23
Internetadresse	https://www.mile-high.video/

Research Field

Ehemaliges Research Field - Experience Measurement

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10.1145/3588444.3591025

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title = "Elevating Your Streaming Experience with Just Noticeable Difference (JND)-based Encoding",

abstract = "With the growing number of video streaming applications, intelligent video streaming has become increasingly important. By considering JND, video delivery can be improved by avoiding the selection of encodings with similar quality for a bitrate ladder. In this paper, we present an overview of the existing methods for modeling and predicting JND in the context of video streaming applications.",

keywords = "Just Noticeable Difference (JND), Satisfied User Ratio (SUR)",

author = "Jingwen Zhu and H. Amirpour and Menon, \{Vignesh V\} and Raimund Schatz and \{Le Callet\}, Patrick",

note = "Q2 2023; ACM MILE-HIGH VIDEO 2023 ; Conference date: 07-05-2023 Through 10-05-2023",

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doi = "10.1145/3588444.3591025",

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AU - Le Callet, Patrick

N1 - Q2 2023

PY - 2023/6/16

Y1 - 2023/6/16

N2 - With the growing number of video streaming applications, intelligent video streaming has become increasingly important. By considering JND, video delivery can be improved by avoiding the selection of encodings with similar quality for a bitrate ladder. In this paper, we present an overview of the existing methods for modeling and predicting JND in the context of video streaming applications.

AB - With the growing number of video streaming applications, intelligent video streaming has become increasingly important. By considering JND, video delivery can be improved by avoiding the selection of encodings with similar quality for a bitrate ladder. In this paper, we present an overview of the existing methods for modeling and predicting JND in the context of video streaming applications.

KW - Just Noticeable Difference (JND)

KW - Satisfied User Ratio (SUR)

U2 - 10.1145/3588444.3591025

DO - 10.1145/3588444.3591025

M3 - Conference Proceedings with Oral Presentation

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T3 - MHV '23

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BT - Proceedings of the 2nd Mile-High Video Conference

CY - New York, NY, USA

T2 - ACM MILE-HIGH VIDEO 2023

Y2 - 7 May 2023 through 10 May 2023

ER -

Elevating Your Streaming Experience with Just Noticeable Difference (JND)-based Encoding

Abstract

Publikationsreihe

Konferenz

Research Field

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