Enhancing QoE for Viewport-Adaptive 360-Degree Video Streaming: Perception Analysis and Implementation

Abstract

Viewport-adaptive streaming is now a widely embraced solution for transmission of 360-degree video, where users perceptual quality after their head movement suffers from the temporary exposure of a low-quality area, as well as the related delay in quality refinement. In this article, subjective experiments were conducted to investigate the humans perception of quality refinement in viewport-adaptive 360-degree video streaming, considering the saccadic suppression, foveal vision, and contrast sensitivity of the human visual system. According to the experimental results, a measurement of the Just Noticeable Refinement Delay is proposed to describe the delay when quality refinement is just noticeable. Based on the findings in perception analysis, a real-time adaptive 360-degree video streaming system using the Random Access Reference Frame is proposed, which can dramatically reduce the refinement delay to enhance users quality of experience. Experimental results demonstrated that the proposed system provide better QoE to users compared to the traditional viewport-adaptive 360-degree video streaming system.