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Fuzzy Logic-Based Adaptive Point Cloud Video Streaming
IEEE Open Journal of the Computer Society Pub Date : 2020-07-01 , DOI: 10.1109/ojcs.2020.3006205
Zhi Liu , Jie Li , Xianfu Chen , Celimuge Wu , Susumu Ishihara , Yusheng Ji , Jie Li

Point cloud video provides 6 degrees of freedom (6DoF) viewing experiences to allow users to freely select the viewing angles of 3D scenes and is expected to be the next-generation video. This paper studies the point cloud video streaming and proposes a fuzzy logic-based point cloud video streaming scheme to solve the inherent technical issues. In particular, a point cloud video is first partitioned into smaller tiles, along with a low-quality base layer covering the entire video. Each tile is encoded into different quality levels, and both the compressed and uncompressed (i.e., decoded) versions of each tile are prepared for selection. Then, based on the user's viewing angle and predicted future network bandwidth condition, fuzzy logic empowered quality level selection, with properly defined novel fuzzification, fuzzy rules , and defuzzification , is conducted to maximize the received point cloud video quality under the communication resource, computational resource and quality requirements constraints. Extensive simulations based on real point cloud video sequences and network traces are conducted, and the results reveal the superiority of the proposed scheme over the baseline scheme. To the best of our knowledge, this is the first work studying point cloud video streaming using fuzzy logic.

中文翻译:

基于模糊逻辑的自适应点云视频流

点云视频可提供6个自由度(6DoF)的观看体验,以允许用户自由选择3D场景的观看角度,有望成为下一代视频。本文研究了点云视频流,提出了一种基于模糊逻辑的点云视频流方案,以解决内在的技术问题。具体而言,首先将点云视频与覆盖整个视频的低质量基础层一起划分为较小的图块。每个图块被编码为不同的质量级别,并且每个图块的压缩和未压缩(即,解码)版本都准备好进行选择。然后,基于用户的视角和预测的未来网络带宽状况,模糊逻辑可实现质量级别选择,并定义适当的新颖性模糊化,模糊规则去模糊化 在通信资源,计算资源和质量要求约束下进行,以使接收点云视频质量最大化。进行了基于实点云视频序列和网络轨迹的广泛仿真,结果表明了该方案相对于基线方案的优越性。据我们所知,这是使用模糊逻辑研究点云视频流的第一项工作。
更新日期:2020-07-17
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