Content-based subjective quality prediction in stereoscopic videos with machine learning

Malekmohamadi, Hossein and Fernando, W. A. C. and Kondoz, A. M. (2012) Content-based subjective quality prediction in stereoscopic videos with machine learning. Electronics Letters, 48 (21). pp. 1344-1345. ISSN 0013-5194

Full content URL: http://dx.doi.org/10.1049/el.2012.2365

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Item Type:Article
Item Status:Live Archive

Abstract

A model exploiting machine learning and content analysis is proposed to predict the subjective quality of stereoscopic videos. This model offers an automated, accurate and consistent subjective quality prediction. The feasibility and accuracy of the proposed technique has been thoroughly analysed with extensive subjective experiments and simulations. Results illustrate that a performance measure of 0.954 in subjective quality prediction can be achieved with the proposed technique.

Keywords:content analysis, content-based subjective quality prediction, machine learning, stereoscopic video
Subjects:G Mathematical and Computer Sciences > G400 Computer Science
Divisions:College of Science > School of Computer Science
ID Code:12751
Deposited On:20 Dec 2013 10:06

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