Automatic QOE prediction in stereoscopic videos

Malekmohamadi, Hossein and Fernando, W. A. C. and Kondoz, A. M. (2012) Automatic QOE prediction in stereoscopic videos. In: 2012 IEEE International Conference on Multimedia and Expo Workshops (ICMEW), 9-13 July 2012, Melbourne, Victoria, Australia.

Full content URL: http://dx.doi.org/10.1109/ICMEW.2012.107

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Item Type:Conference or Workshop contribution (Paper)
Item Status:Live Archive

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.

Keywords:Discriminant analysis, K-means clustering, QoE, SAMVIQ, Video quality metric
Subjects:G Mathematical and Computer Sciences > G400 Computer Science
Divisions:College of Science > School of Computer Science
ID Code:12752
Deposited On:20 Dec 2013 10:15

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