QoE Optimization in DASH-Based Multiview Video Streaming

Abstract

Multiview video based on Dynamic Adaptive Streaming over HTTP (DASH) allows users to freely navigate between available viewpoints. However, achieving seamless transition during viewpoint switching is still challenging, especially in free-viewpoint video streaming, where user navigation is unpredictable. When bandwidth is limited, delivering all viewpoints in high quality is nearly impossible. The streaming system needs to prioritize high video quality for the selected viewpoint. The problem arises when the switching event occurs because the new video may not yet be available in the buffer. This paper introduces multiview video quality of experience (QoE). We discuss how viewpoint transition delay and viewpoint quality delay affect the overall user experience in watching multiview videos. We propose quality-based adaptive bitrate (ABR) for multiview video by specifying viewpoint priority and a target quality of the main viewpoint, namely multiview video priority (MVP). Although it may select a lower bitrate level than rate-based ABR, it performs better in perceptual video quality, especially when the viewpoint changes frequently. The simulation results show that the MVP algorithm effectively allocates available bandwidth to the required viewpoints. Hence, it can eliminate transition delay and decrease viewpoint quality delay. As a result, the user gets better video quality, smoothness, continuity, and seamless transition during video switching.