QoE evaluation methods for 360-degree VR video transmission

Virtual reality (VR) videos, especially 360-degree VR videos, have attracted substantial research interests with the explosion of mobile VR devices in recent years. In this work, we propose a VR quality of experience (QoE) evaluation framework including online, offline and mixed scenarios that can meet the requirement of real applications. Under this framework, we further develop a subjective evaluation method and an objective QoE evaluation model based on network transmission parameters. A VR panoramic video database is established with nine different contents. This database contains 468 different samples coming from nine original contents. Then, in the subjective evaluation part, we propose to adopt four dimensions, i.e., quality score, immersion score, non-spinning sensation score and global score for the subjective evaluation purpose. These dimensions can meet the interaction and immersion features of the VR video service. In the objective evaluation part, an improved two-step neural network (INN) model is developed by using the features of the physiological psychology and cognitive neurology. This model captures the intrinsic link between the initial input network parameters and the final perception in VR transmission. Our results suggest that the proposed INN can achieve a higher pearson correlation coefficients than the other methods. Especially, it increases by 8.9% than the traditional NN method. Our work can make up for the shortage of traditional evaluation methods in term of the VR QoE subjective and objective evaluation in transmission scopes.