REEFT-360: Real-time Emulation and Evaluation Framework for Tile-based 360 Streaming under Time-varying Conditions

Abstract

With 360° video streaming, the user s field of view (a.k.a. viewport) is at all times determined by the user s current viewing direction. Since any two users are unlikely to look in the exact same direction as each other throughout the viewing of a video, the frame-by-frame video sequence displayed during a playback session is typically unique. This complicates the direct comparison of the perceived Quality of Experience (QoE) using popular metrics such as the Multiscale-Structural Similarity (MS-SSIM). Furthermore, there is an absence of light-weight emulation frameworks for tiled-based 360° video streaming that allow easy testing of different algorithm designs and tile sizes. To address these challenges, we present REEFT-360, which consists of (1) a real-time emulation framework that captures tile-quality adaptation under time-varying bandwidth conditions and (2) a multi-step evaluation process that allows the calculation of MS-SSIM scores and other frame-based metrics, while accounting for the user s head movements. Importantly, the framework allows speedy implementation and testing of alternative head-movement prediction and tile-based prefetching solutions, allows testing under a wide range of network conditions, and can be used either with a human user or head-movement traces. The developed software tool is shared with the paper. We also present proof-of-concept evaluation results that highlight the importance of including a human subject in the evaluation.