A new perceptual evaluation method of video quality based on neural network

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F21%3A10248276" target="_blank" >RIV/61989100:27240/21:10248276 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/61989100:27740/21:10248276

Výsledek na webu

<a href="https://content.iospress.com/articles/intelligent-data-analysis/ida205085" target="_blank" >https://content.iospress.com/articles/intelligent-data-analysis/ida205085</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3233/IDA-205085" target="_blank" >10.3233/IDA-205085</a>

Jazyk výsledku

angličtina

Název v původním jazyce

A new perceptual evaluation method of video quality based on neural network

Popis výsledku v původním jazyce

This paper proposes a novel method for video quality evaluation based on machine learning technique. The current research deals with the correct interpretation of objective video quality evaluation (Quality of Service - QoS) in relation to subjective end-user perception (Quality of Experience - QoE), typically expressed by mean opinion score (MOS). Our method allows us to interconnect results obtained from video objective and subjective assessment methods in the form of a neural network (computing model inspired by biological neural networks). So far, no unified interpretation scale has been standardized for both approaches, therefore it is difficult to determine the level of end-user satisfaction obtained from the objective assessment. Thus, contribution of the proposed method lies in description of the way to create a hybrid metric that delivers fast and reliable subjective score of perceived video quality for internet television (IPTV) broadcasting companies.

Název v anglickém jazyce

A new perceptual evaluation method of video quality based on neural network

Popis výsledku anglicky

This paper proposes a novel method for video quality evaluation based on machine learning technique. The current research deals with the correct interpretation of objective video quality evaluation (Quality of Service - QoS) in relation to subjective end-user perception (Quality of Experience - QoE), typically expressed by mean opinion score (MOS). Our method allows us to interconnect results obtained from video objective and subjective assessment methods in the form of a neural network (computing model inspired by biological neural networks). So far, no unified interpretation scale has been standardized for both approaches, therefore it is difficult to determine the level of end-user satisfaction obtained from the objective assessment. Thus, contribution of the proposed method lies in description of the way to create a hybrid metric that delivers fast and reliable subjective score of perceived video quality for internet television (IPTV) broadcasting companies.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20203 - Telecommunications

Projekt

<a href="/cs/project/LM2018140" target="_blank" >LM2018140: e-Infrastruktura CZ</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Intelligent Data Analysis

ISSN

1088-467X

e-ISSN

—

Svazek periodika

25

Číslo periodika v rámci svazku

3

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

17

Strana od-do

571-587

Kód UT WoS článku

000644439500006

EID výsledku v databázi Scopus

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