QoE Oriented Adaptive Streaming Method for 360° Virtual Reality Videos
PubDate: April 2020
Teams: Wuhan University of Technology；Dublin City University
Writers: Yi Han; Yafeng Ma; Yangzhe Liao; Gabriel-Miro Muntean
Recently streaming virtual reality (VR) video has become increasingly accessible to a growing number of consumers following the rapid development of network capacity and widespread high specification devices. Various solutions have been proposed including adaptive streaming methods for VR videos. However, the high bandwidth requirement of VR videos brings new challenges in designing proper adaptive streaming methods with respect to VR characteristics in terms of both coding and transmission. Streaming VR videos differ from traditional 2D videos as their users’ perceptual Quality of Experience (QoE) is more sensitive to video stalls, quality variations, and as a matter of novelty, viewport dependent. The viewport movement is associated with new issues in adaptive streaming scheme design. In order to adapt to the fast viewport movement and restrict time constraints in VR videos, a tile-based VR video format adjustment is adopted in our research. In this paper, we present Q360AS, a novel adaptive streaming method for 360° VR videos that aims at maximizing the overall QoE during the transmission in environments with varying network conditions. The proposed method shows a notable increase in real-time QoE in comparison to existing adaptive VR video streaming methods.