CNN viewpoint prediction plus Laplace-modeled error yields per-tile visibility probabilities that drive a steepest-descent solver for multi-user 360-video rate allocation, claimed to outperform prior schemes.
A Rate Adaptation Algorithm for Tile-based 360-degree Video Streaming
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abstract
In the 360-degree immersive video, a user only views a part of the entire raw video frame based on her viewing direction. However, today's 360-degree video players always fetch the entire panoramic view regardless of users' head movement, leading to significant bandwidth waste that can be potentially avoided. In this paper, we propose a novel adaptive streaming scheme for 360-degree videos. The basic idea is to fetch the invisible portion of a video at the lowest quality based on users' head movement prediction and to adaptively decide the video playback quality for the visible portion based on bandwidth prediction. Doing both in a robust manner requires overcome a series of challenges, such as jointly considering the spatial and temporal domains, tolerating prediction errors, and achieving low complexity. To overcome these challenges, we first define quality of experience (QoE) metrics for adaptive 360-degree video streaming. We then formulate an optimization problem and solve it at a low complexity. The algorithm strategically leverages both future bandwidth and the distribution of users' head positions to determine the quality level of each tile (i.e., a sub-area of a raw frame). We further provide theoretical proof showing that our algorithm achieves optimality under practical assumptions. Numerical results show that our proposed algorithms significantly boost the user QoE by at least 20\% compared to baseline algorithms.
years
2019 2verdicts
UNVERDICTED 2representative citing papers
Develops a FoV-prediction-based VR video transmission algorithm with adaptive modulation and convex optimization that outperforms other streaming methods in simulations.
citing papers explorer
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Probabilistic Tile Visibility-Based Server-Side Rate Adaptation for Adaptive 360-Degree Video Streaming
CNN viewpoint prediction plus Laplace-modeled error yields per-tile visibility probabilities that drive a steepest-descent solver for multi-user 360-video rate allocation, claimed to outperform prior schemes.
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An Algorithm for Transmitting VR Video Based on Adaptive Modulation
Develops a FoV-prediction-based VR video transmission algorithm with adaptive modulation and convex optimization that outperforms other streaming methods in simulations.