VQBA: Visual-Quality-Driven Bit Allocation for Low-Latency Point Cloud Streaming
VQBA: Visual-Quality-Driven Bit Allocation for Low-Latency Point Cloud Streaming
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VQBA：低延迟点云流的视觉质量驱动的比特分配
DOI：
10.1145/3581783.3612486
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发表时间：
2023
期刊：
影响因子：
--
通讯作者：
Liu, Yao
中科院分区：
文献类型：
--
作者：
Wang, Shuoqian;Zhu, Mufeng;Li, Na;Xiao, Mengbai;Liu, Yao
基于视频的点云压缩(V-PCC)是一种新兴的动态点云数据编码标准。使用V-PCC，点云数据被分割、投影并打包到2D视频帧上，可以使用现有的视频编码标准(如H.264、H.265和AV1)进行压缩。这使得通过可靠的视频传输系统支持点云流成为可能。另一方面，尽管最近取得了一些进展，但仍然存在许多问题，阻碍了V-PCC在低延迟点云流中的使用。例如，点云配准和面片生成需要很长的时间。本文重点研究了V-PCC中的一个独特问题：不同子流-几何子流和属性(颜色)子流-之间的比特分配，目标是在目标比特率下提高点云的视觉质量。现有的方法要么没有充分利用可用带宽，要么运行时间较长，不能用于需要低延迟的场景。为此，我们提出了一种轻量级的、基于频域的剖面法，将动态点云数据转换为一维向量。通过使用两个单层线性回归模型，我们可以估计几何数据和颜色信息的压缩比特率。这允许我们通过简单的计算在几何图和属性图之间执行位分配。评估结果表明，与基线方法相比，该方法在目标码率下能够以较小的编码片段尺寸获得更好的视觉质量。
Video-based Point Cloud Compression (V-PCC) is an emerging standard for encoding dynamic point cloud data. With V-PCC, point cloud data is segmented, projected, and packed on to 2D video frames, which can be compressed using existing video coding standards such as H.264, H.265 and AV1. This makes it possible to support point cloud streaming via reliable video transmission systems. On the other hand, despite recent advances, many issues still remain and prevent V-PCC from being used in low-latency point cloud streaming. For instance, point cloud registration and patch generation can take a long time.In this paper, we focus on one unique problem in V-PCC: bit allocation among different sub-streams - the geometry sub-stream and the attribute (color) sub-stream - with the goal of improving the visual quality of point clouds under the target bitrate. Existing approaches either do not fully utilize the available bandwidth or can take a long time to run, which cannot be used in scenarios that require low-latency. To this end, we propose a lightweight, frequency-domain-based profiling method for transforming the dynamic point cloud data into a one-dimension vector. By using two single-layer linear regression models, we can estimate the compressed bitrate for geometry data and color information. This allows us to perform bit allocation between the geometry map and the attribute map with simple calculations. Evaluation results show that compared to the baseline approach, our method can achieve better visual qualities with smaller encoded segment sizes under the target bitrate.
DOI：
10.1109/jetcas.2018.2885981
发表时间：
2019-03-01
影响因子：
4.6
作者：
Schwarz, Sebastian;Preda, Marius;Zakharchenko, Vladyslav
通讯作者：
Zakharchenko, Vladyslav