DWS-BEAM:基于解码器的MPEG沉浸式视频子图像比特流提取和合并

2021 International Conference on Visual Communications and Image Processing (VCIP) Pub Date : 2021-12-05 DOI:10.1109/VCIP53242.2021.9675419

Jong-Beom Jeong, Soonbin Lee, Eun‐Seok Ryu

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引用次数: 7

摘要

随着新的沉浸式视频编码标准MPEG(沉浸式视频编码)和通用视频编码(VVC)的出现，计算机生成和自然内容视频的六自由度虚拟现实(VR)流媒体技术正在兴起。本文讨论了用于MIV的解码器智能子图像比特流提取和合并(DWS-BEAM)方法，并提出了两个主要思想:(i)使用运动约束贴图集(MCTS)的选择性流感知子图像分配方法，(ii)用于单次解码的解码器智能子图像提取和合并方法。在使用VVC测试模型(VTM)的实验中，与VTM锚点相比，所提出的方法在沉浸式视频PSNR (IV-PSNR)上节省了1.23%的bd率，在解码时间上节省了15.78%。此外，MIV测试模型需要四个解码器，而本文方法只需要一个解码器。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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DWS-BEAM: Decoder-Wise Subpicture Bitstream Extracting and Merging for MPEG Immersive Video

With the new immersive video coding standard MPEG immersive video (MIV) and versatile video coding (VVC), six degrees of freedom (6DoF) virtual reality (VR) streaming technology is emerging for both computer-generated and natural content videos. This paper addresses the decoder-wise subpicture bitstream extracting and merging (DWS-BEAM) method for MIV and proposes two main ideas: (i) a selective streaming-aware subpicture allocation method using a motion-constrained tile set (MCTS), (ii) a decoder-wise subpicture extracting and merging method for single-pass decoding. In the experiments using the VVC test model (VTM), the proposed method shows 1.23% BD-rate saving for immersive video PSNR (IV-PSNR) and 15.78% decoding runtime saving compared to the VTM anchor. Moreover, while the MIV test model requires four decoders, the proposed method only requires one decoder.

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来源期刊

2021 International Conference on Visual Communications and Image Processing (VCIP)

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