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Viewport-Aware Omnidirectional Video Streaming Using Visual Attention and Dynamic Tiles

机译:使用视觉注意力和动态图块的视口感知全向视频流

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In this paper, we introduce a new adaptive omnidirectional video (ODV) streaming system that uses visual attention (VA) maps, providing enhanced virtual reality (VR) video experiences. Our proposed method benefits from dynamic tiling and viewport-aware bitrate allocation algorithms. Our main contribution is utilizing the VA maps for deciding the tiling structure (i.e., tile scheme) per chunk and distributing a given bitrate budget to each tile in a viewport-aware way. For this, we first estimate viewport-based VA maps using the collected users' viewport trajectories. Then, an optimal pair of tiling scheme and unequal bitrate allocation for each tile of a given content is determined per chunk by calculating the expected viewport quality using our proposed VA-weighted objective quality measurement (OmniVA). We evaluate the proposed method performance with varying bandwidth conditions and viewport trajectories from different users. The results show that the proposed method significantly outperforms the existing tiled-based method in terms of viewport-PSNR.
机译:在本文中,我们介绍了一种新的自适应全向视频(ODV)流传输系统,该系统使用视觉注意(VA)映射,从而提供增强的虚拟现实(VR)视频体验。我们提出的方法得益于动态切片和可识别视口的比特率分配算法。我们的主要贡献是利用VA映射来确定每个块的切片结构(即切片方案),并以视口感知的方式将给定的比特率预算分配给每个切片。为此,我们首先使用收集的用户的视口轨迹估算基于视口的VA地图。然后,通过使用我们建议的VA加权客观质量测量(OmniVA)计算预期的视口质量,为每个块确定最佳的平铺方案对和给定内容的每个图块的不相等比特率分配。我们用不同的带宽条件和来自不同用户的视口轨迹来评估所提出的方法的性能。结果表明,该方法在视口PSNR方面明显优于现有的基于平铺方法。

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