Dragonfly: Higher Perceptual Quality For Continuous 360 Video Playback

When streaming 360 degrees video, it is possible to reduce bandwidth by 5x with approaches that spatially segment video into tiles and only stream the user's viewport. Unfortunately, it is difficult to accurately predict a user's viewport even 2-3 seconds before playback. This results in rebuffering events owing to misprediction of a user's viewport or network bandwidth dips, which hurts interactive experience. However, avoiding rebuffering by naively skipping tiles that do not arrive by the playback deadline may lead to incomplete viewports and degraded experience. In this paper, we describe Dragonfly, a new 360 degrees system that preserves interactive experience by avoiding playback stalls while maintaining high perceptual quality. Dragonfly prudently skips tiles using a model that defines an overall utility function to decide which tiles to fetch, and at which qualities they should be fetched, with the goal of optimizing user experience. To minimize incomplete viewports, it also fetches a low quality masking stream. Using a user study with 26 users and emulation-based experiments we show that Dragonfly has higher quality, and lower overheads, than state-of-the-art 360 degrees streaming approaches. For instance, in our study, 65% of sessions have a rating of 4 or higher (Good/Excellent) with Dragonfly, while only 16% of sessions with Pano, and 13% of sessions with Flare achieve this rating.