PCQD‐AR: Subjective quality assessment of compressed point clouds with head‐mounted augmented reality

Abstract

AbstractThis letter fully studies the coloured point cloud quality assessment in augmented reality (AR) environment through subjective test. Firstly, a point cloud dataset, named point cloud quality dataset‐AR, including ten reference point clouds and their 90 distorted versions is presented, which were generated using the reference software of video‐based point cloud compression across various combinations of geometry and texture quantization parameters. Then, the impact of geometry and texture distortions on perceived quality of point clouds in AR environment was discussed in detail. Moreover, the performance of existing objective point cloud quality assessment metrics on the proposed dataset is evaluated. The subjective dataset including the values of mean opinion score were released to public.