自适应体积视频流平台

Srinivas Gudumasu, Yong He, J. Fleureau
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引用次数: 1

摘要

本文提出了一种包括实时跟踪、自适应源视图选择、DASH流、GPU加速视图合成、HEVC解码和视图依赖渲染在内的自适应体视频流平台。体积用例支持3个自由度的身临其境的体验与额外的有限的平移运动。所提出的自适应流媒体平台基于先进的视图合成技术和基于dash的自适应流媒体,以增强沉浸式体验,同时降低整体传输带宽。GPU加速进一步支持实时视图合成,HEVC解码和视图渲染。仿真结果验证了所提出的自适应方案能够更有效地利用带宽。因此,可以向用户提供具有高质量容量视频内容和低交互延迟的更一致的观看体验。该平台已于2019年4月在2019年世界移动通信大会和第二届VR生态系统和标准研讨会上进行了演示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adaptive Volumetric Video Streaming Platform
This paper proposes an adaptive volumetric video streaming platform including real-time tracking, adaptive source view selection, DASH streaming, GPU accelerated view synthesis, HEVC decoding and view-dependent rendering. Volumetric use case supports 3 degree of freedom immersive experience with additional limited translational movement. The proposed adaptive streaming platform is built on advanced view synthesis technologies and DASH-based adaptive streaming to enhance the immersive experience while reducing the overall transmission bandwidth. The GPU acceleration further enables real-time view synthesis, HEVC decoding and view rendering. The simulation results verify that the proposed adaptive solution can utilize the bandwidth more efficiently. As a result, a more consistent viewing experience with high quality volumetric video content and low interactive latency can be delivered to the user. The platform has been demonstrated in the 2019 Mobile World Congress and 2nd VR ecosystems and standards workshop in April 2019.
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