Predictive Tile Selection for 360-Degree VR Video Streaming in Bandwidth-Limited Networks

To stream 360-degree video bandwidth-efficiently to virtual reality users, only a subset of a video's spatial tiles corresponding to the current viewport of a user can be transferred, but tile selection is challenging since a user's viewport keeps moving over time. In this letter, we find that the error distribution of fixation point prediction is formally derived as a normal distribution. Based on this theoretical finding, the region where a user's future viewport is likely to reside with a given confidence level is obtained in a closed form and the proposed algorithm selects tiles covering the region.