Synergistic Temporal-Spatial User-Aware Viewport Prediction for Optimal Adaptive 360-Degree Video Streaming

视区 计算机科学 学位(音乐) 视频流媒体 实时计算 多媒体 计算机图形学(图像) 物理 声学
作者
Yumei Wang,Junjie Li,Zhijun Li,Simou Shang,Yu Liu
出处
期刊:IEEE Transactions on Broadcasting [Institute of Electrical and Electronics Engineers]
卷期号:70 (2): 453-467 被引量:3
标识
DOI:10.1109/tbc.2024.3374119
摘要

360-degree videos usually require extremely high bandwidth and low latency for wireless transmission, which hinders their popularity. A tile-based viewport adaptive streaming scheme, which involves accurate viewport prediction and optimal bitrate adaptation to maintain user Quality of Experience (QoE) under a bandwidth-constrained network, has been proposed by researchers. However, viewport prediction is error-prone in long-term prediction, and bitrate adaptation schemes may waste bandwidth resources due to failing to consider various aspects of QoE. In this paper, we propose a synergistic temporal-spatial user-aware viewport prediction scheme for optimal adaptive 360-Degree video streaming (SPA360) to tackle these challenges. We use a user-aware viewport prediction mode, which offers a white box solution for Field of View (FoV) prediction. Specially, we employ temporal-spatial fusion for enhanced viewport prediction to minimize prediction errors. Our proposed utility prediction model jointly considers viewport probability distribution and metrics that directly affecting QoE to enable more precise bitrate adaptation. To optimize bitrate adaptation for tiled-based 360-degree video streaming, the problem is formulated as a packet knapsack problem and solved efficiently with a dynamic programming-based algorithm to maximize utility. The SPA360 scheme demonstrates improved performance in terms of both viewport prediction accuracy and bandwidth utilization, and our approach enhances the overall quality and efficiency of adaptive 360-degree video streaming.
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