Prediction of perceptual quality for mobile video using fuzzy inference systems

Along with the rapid growth in consumer adoption of modern portable devices, video streaming is expected to dominate a large share of the global internet traffic in the near future. In the wireless communications domain, this trend creates considerable challenges to consumers´ quality of experience (QoE). From a consumer-focused vision, predicting perceptual video quality is extremely important for QoE-based service provisioning. However, available QoE measurement techniques that adopt a full reference model are impractical in real-time transmission since they require the original video sequence to be available at the receiver´s end. Therefore, the primary aim of this study is to present a cross-layer no-reference prediction model for the perceptual quality of 3D video in the wireless domain. The contributions of this study are twofold: first, the impact of selected quality of service (QoS) parameters from both encoding and network levels on QoE is investigated. Also, the obtained QoS/QoE correlation is backed by thorough statistical analysis. Second, a prediction model based on fuzzy logic inference systems (FIS) is developed by mapping chosen QoS parameters to the measured QoE. This model enables a non-intrusive prediction of 3D visual quality. Conclusive results show a significantly high correlation between the predicted video quality and the objectively measured mean opinion scores (MOS). Objective MOS is also validated through methodical subjective assessments. For consumer´s QoE, this study advances the development of reference-free video quality prediction models and QoE control methods for 3D video streaming.