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Automatic QOE prediction in stereoscopic videos

Malekmohamadi, H, Fernando, WAC and Kondoz, AM (2012) Automatic QOE prediction in stereoscopic videos

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Abstract

In this paper, we propose a method for automatic quality of experience (QoE) prediction in stereoscopic videos. QoE, though embodying the subjective measures of the end user's perceived quality, can be expressed in relation to some quality of service (QoS) parameters. Having information on content types in modelling QoE-QoS interactions is advantageous as videos with the same QoS parameters may have different subjective scores due to different content types. Consequently, using content clustering with the help of spatio-temporal activities within depth layers, QoE predictor is designed per each content cluster utilising full reference (FR) and no reference (NR) metrics. Finally, the performance of the proposed QoE prediction algorithm is evaluated extensively and the overall measure of success value equal to 95.4% is achieved for the test sequences. This model can be applied for QoE control in video provisioning systems. © 2012 IEEE.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Authors :
NameEmailORCID
Malekmohamadi, HUNSPECIFIEDUNSPECIFIED
Fernando, WACw.fernando@surrey.ac.ukUNSPECIFIED
Kondoz, AMa.kondoz@surrey.ac.ukUNSPECIFIED
Date : 2012
Identification Number : 10.1109/ICMEW.2012.107
Depositing User : Symplectic Elements
Date Deposited : 17 May 2017 12:35
Last Modified : 17 May 2017 15:04
URI: http://epubs.surrey.ac.uk/id/eprint/835908

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