Block-Based Inter-Frame Prediction For Dynamic Point Cloud Compression
Block-Based Inter-Frame Prediction For Dynamic Point Cloud Compression
复制标题
用于动态点云压缩的基于块的帧间预测
DOI：
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发表时间：
2021
期刊：
影响因子：
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通讯作者：
M. Porto
中科院分区：
文献类型：
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作者：
Cristiano Santos;Mateus M. Gonçalves;G. Corrêa;M. Porto
近年来，由于技术进步，如计算能力的提高和用于获取3D信息的低成本设备（如RGBD传感器）的可用性，3D点云得到了普及。然而，原始点云需要大量的数据来表示，并且压缩是强制性的，以允许有效的传输和存储。帧间预测是在2D视频编码器中实现高压缩率的广泛使用的方法，但是当前文献仍然缺乏有效地利用时间冗余用于点云编码的解决方案。在这项工作中，我们提出了一种新的帧间预测的三维点云压缩，探讨在三维空间中的时间冗余。此外，还提出了一种模式决策算法，在帧间预测和帧内预测之间动态选择最佳编码模式。所提出的方法产生的几何和亮度信息的比特率分别减少15.6%和3.5%，与MPEG 3DG的解决方案相比，没有显着的影响，在客观质量，称为G-PCC。
In recent years, 3D point clouds have gained popularity thanks to technological advances such as the increased computational power and the availability of low-cost devices for acquisition of 3D information, like RGBD sensors. However, raw point clouds demand a large amount of data for their representation, and compression is mandatory to allow efficient transmission and storage. Inter-frame prediction is a widely used approach to achieve high compression rates in 2D video encoders, but the current literature still lacks solutions that efficiently exploit temporal redundancy for point cloud encoding. In this work, we propose a novel inter-frame prediction for 3D point cloud compression, which explores temporal redundancies in the 3D space. Moreover, a mode decision algorithm is also proposed to dynamically choose the best encoding mode between inter and intra prediction. The proposed method yields a bitrate reduction of 15.6% and 3.5% for geometry and luma information respectively, with no significant impact in objective quality when compared to the MPEG 3DG solution, called G-PCC.