  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.
