论文标题
广义基于豪斯多夫的基于距离的质量指标，用于点云几何形状
A generalized Hausdorff distance based quality metric for point cloud geometry
论文作者
论文摘要
对解码点云几何形状的可靠质量评估对于评估新兴点云编码解决方案的压缩性能并保证某些目标经验质量至关重要。本文提出了基于Hausdorff距离的概括的新点云几何质量评估度量。为了实现这一目标，利用了所谓的多个排名的普通豪斯多夫距离，以确定与从主观测试活动中获得的MOS分数相关的最佳性能质量指标。实验结果表明，从经典的Hausdorff距离得出的质量度量导致客观主体相关性较低，因此无法准确评估新兴编解码器的解码点云的质量。但是，考虑到具有不同类型的编码变形类型的解码点云时，从广义的Hausdorff距离得出的具有适当选择的排名的广义距离距离。
Reliable quality assessment of decoded point cloud geometry is essential to evaluate the compression performance of emerging point cloud coding solutions and guarantee some target quality of experience. This paper proposes a novel point cloud geometry quality assessment metric based on a generalization of the Hausdorff distance. To achieve this goal, the so-called generalized Hausdorff distance for multiple rankings is exploited to identify the best performing quality metric in terms of correlation with the MOS scores obtained from a subjective test campaign. The experimental results show that the quality metric derived from the classical Hausdorff distance leads to low objective-subjective correlation and, thus, fails to accurately evaluate the quality of decoded point clouds for emerging codecs. However, the quality metric derived from the generalized Hausdorff distance with an appropriately selected ranking, outperforms the MPEG adopted geometry quality metrics when decoded point clouds with different types of coding distortions are considered.
