Optimal Mapping Function for Predictions of the Subjective Quality Evaluation Using Artificial Intelligence
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F19%3A10243549" target="_blank" >RIV/61989100:27740/19:10243549 - isvavai.cz</a>
Výsledek na webu
<a href="https://link.springer.com/chapter/10.1007/978-3-030-32520-6_21" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-030-32520-6_21</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-32520-6_21" target="_blank" >10.1007/978-3-030-32520-6_21</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Optimal Mapping Function for Predictions of the Subjective Quality Evaluation Using Artificial Intelligence
Popis výsledku v původním jazyce
With the growth of QoE interest, IPTV providers need a method to control QoE. The paper describes the correlation between the results of objective and subjective methods in video quality assessment. The authors proposed the optimal mapping function for predictions of the subjective quality evaluation based on the objective evaluation to determine the perception of the video quality by the human brain. Our model using artificial intelligence, it is based on a neural network which can simulate and predicts the subjective quality of the scene. It also can predict subjective or objective video quality for video sequences defined by spatial, temporal information, which is the critical and key variable of a given scene, and by the qualitative parameters of the scene. The results from the model are verified by comparing predicted video quality using the proposed classifier with the required value. The two most common statistical parameters related to express performance are Pearson's correlation coefficient and Root Mean Square Error. (C) 2020, Springer Nature Switzerland AG.
Název v anglickém jazyce
Optimal Mapping Function for Predictions of the Subjective Quality Evaluation Using Artificial Intelligence
Popis výsledku anglicky
With the growth of QoE interest, IPTV providers need a method to control QoE. The paper describes the correlation between the results of objective and subjective methods in video quality assessment. The authors proposed the optimal mapping function for predictions of the subjective quality evaluation based on the objective evaluation to determine the perception of the video quality by the human brain. Our model using artificial intelligence, it is based on a neural network which can simulate and predicts the subjective quality of the scene. It also can predict subjective or objective video quality for video sequences defined by spatial, temporal information, which is the critical and key variable of a given scene, and by the qualitative parameters of the scene. The results from the model are verified by comparing predicted video quality using the proposed classifier with the required value. The two most common statistical parameters related to express performance are Pearson's correlation coefficient and Root Mean Square Error. (C) 2020, Springer Nature Switzerland AG.
Klasifikace
Druh
D - Stať ve sborníku
CEP obor
—
OECD FORD obor
20203 - Telecommunications
Návaznosti výsledku
Projekt
<a href="/cs/project/LM2015070" target="_blank" >LM2015070: IT4Innovations národní superpočítačové centrum</a><br>
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Ostatní
Rok uplatnění
2019
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název statě ve sborníku
Advances in Intelligent Systems and Computing. Volume 1069
ISBN
978-3-030-32519-0
ISSN
2194-5357
e-ISSN
2194-5365
Počet stran výsledku
13
Strana od-do
263-275
Název nakladatele
Springer
Místo vydání
Cham
Místo konání akce
San Francisco
Datum konání akce
24. 10. 2019
Typ akce podle státní příslušnosti
WRD - Celosvětová akce
Kód UT WoS článku
—