An Adaptive Neuro-Fuzzy Model for Quality Estimation in Wireless 2D/3D Video Streaming Systems

Abstract

Delivering high Quality of Experience (QoE) is essential to the success of today’s subscription for internet video streaming services. Quality of Service (QoS) metrics are considered by the research community as the most influential factor on video QoE. Therefore, establishing QoS-QoE correlation becomes critical for improving video QoE estimation. This paper presents experimental development of effective correlation between QoE and QoS for both 2D and 3D video streaming services. This is then used to build an objective QoE estimation model for real-time streaming of both 2D and 3D video contents over wireless networks. This model is based on using Adaptive Neural Fuzzy Inference System (ANFIS) to estimate the perceived video QoE. The proposed QoE model was trained with a set of media and packet layers’ metrics, taking into account the effect of video content type, dimension, and different packet loss metrics. The performance of the proposed QoE estimation model shows a considerable estimation accuracy with a correlation coefficient of 92% and 0.167 RMSE.