PCQD-AR: Subjective Quality Assessment of Compressed Point Clouds with
Head-mounted Augmented Reality
In this letter, the colored point cloud quality assessment in Augmented
Reality (AR) environment was fully studied through subjective test.
Firstly, we present a point cloud dataset, named Point Cloud Quality
Dataset-AR (PCQD-AR), including ten reference point clouds and their 90
distorted versions, which were encoded by the reference software of
Video-based Point Cloud Compression (V-PCC) under different pairs of
geometry and texture quantization parameters. Then, the impact of
geometry and texture distortions on perceived quality of point clouds in
the AR environment was discussed in detail. Moreover, we evaluate the
performance of existing objective point cloud quality assessment metrics
on the proposed dataset. The subjective dataset including the values of
Mean Opinion Score (MOS) will be released after acceptance.