Optimal Mapping Function for Predictions of the Subjective Quality Evaluation Using Artificial Intelligence

Result code in 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>
Result on the web
<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>

Result language
angličtina
Original language name
Optimal Mapping Function for Predictions of the Subjective Quality Evaluation Using Artificial Intelligence
Original language description
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.
Czech name
—
Czech description
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Project
<a href="/en/project/LM2015070" target="_blank" >LM2015070: IT4Innovations National Supercomputing Center</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Advances in Intelligent Systems and Computing. Volume 1069
ISBN
978-3-030-32519-0
ISSN
2194-5357
e-ISSN
2194-5365
Number of pages
13
Pages from-to
263-275
Publisher name
Springer
Place of publication
Cham
Event location
San Francisco
Event date
Oct 24, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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