基于6DoF头戴式显示器的压缩点云主观质量数据库与客观研究
Subjective Quality Database and Objective Study of Compressed Point Clouds With 6DoF Head-Mounted Display
AI总结：
该研究构建了含340个失真样本的6DoF沉浸式点云主观质量数据库SIAT-PCQD，提出两种基于投影的客观PCQA方法，为点云处理及VR应用提供支撑。
摘要：
本文聚焦沉浸式环境下的主观与客观点云质量评估（PCQA），研究几何与纹理属性在压缩失真中的影响。我们借助具有六自由度的头戴式显示器（HMD），构建了一个主观PCQA数据库，命名为SIAT点云质量数据库（SIAT-PCQD）。该数据库包含340个经MPEG点云编码器压缩的失真点云，由20个序列与17组几何、纹理量化参数组合生成。本文进一步探讨了失真的几何与纹理属性带来的影响。随后，我们提出了两种基于投影的客观质量评估方法，即加权视图投影模型与块投影模型。我们的主观数据库及研究发现可应用于点云处理、传输与编码，尤其适用于虚拟现实场景。该主观数据集已在公共代码仓库发布。
英文摘要：
In this paper, we focus on subjective and objective Point Cloud Quality Assessment (PCQA) in an immersive environment and study the effect of geometry and texture attributes in compression distortion. Using a Head-Mounted Display (HMD) with six degrees of freedom, we establish a subjective PCQA database, named SIAT Point Cloud Quality Database (SIAT-PCQD). Our database consists of 340 distorted point clouds compressed by the MPEG point cloud encoder with the combination of 20 sequences and 17 pairs of geometry and texture quantization parameters. The impact of distorted geometry and texture attributes is further discussed in this paper. Then, we propose two projection-based objective quality evaluation methods, i.e., a weighted view projection based model and a patch projection based model. Our subjective database and findings can be used in point cloud processing, transmission, and coding, especially for virtual reality applications. The subjective dataset has been released in the public repository.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
