Depth Perception Prediction of 3D Video QoE for Future Internet Services

Abstract

3 Dimensional (3D) video Quality of Experience (QoE) metrics are at utmost importance to enable enhancement of Future Internet Services. This enhancement can only be supported when the 3D video is characterized in the most reliable way as possible in these metrics. In light of this fact, a QoE metric including significant depth level and aerial perspective cue to support this reliable way is developed to predict the depth perception of the 3D video. Considering that No Reference (NR) QoE metric type is the most efficient one compared to the other types (i.e., Full Reference (FR) and Reduced Reference (RR)) in terms of transmission requirement, it is used as the metric type to develop the proposed metric. Conducted subjective experiments which are currently the "gold standard" in terms of reliable depth perception assessment are exploited to assess the performance of the proposed metric. Observing the effectiveness of the performance results, it can be clearly concluded that the advancement of the 3D video communication technologies can be ensured to assist Future Internet Services in a timely fashion.