Quality assessment of windowed 6DoF video with viewpoint switching

Abstract

Windowed six degrees of freedom (6DoF) video systems can provide users with highly interactive experiences by offering three rotational and three translational free movements. Free viewing in immersive scenes requires extensive viewpoint switching, which introduces new distortions (such as jitter and discomfort) to windowed 6DoF videos in addition to traditional compression and rendering distortions. This paper proposes a quality assessment method via spatiotemporal features and view switching smoothness for windowed 6DoF-synthesized videos with a wide field of view. Firstly, the edges are extracted from video frames to obtain local spatial distortion features by measuring their statistical characteristics through a generalized Gaussian distribution. Then, the synthesized videos are decomposed and reassembled in the temporal domain to intuitively describe the horizontal and vertical characteristics of the temporal distortions. A gradient-weighted local binary pattern is used to measure temporal flicker distortions. Next, to assess the impact of viewpoint switching on visual perception, a velocity model for retinal image motion is established. Finally, the objective quality score is predicted by a weighted regression model. The experimental results confirm that the proposed method is highly competitive.