Towards subjective quality assessment of point cloud imaging in augmented reality

Recently, there has been an increased interest in capture, processing and rendering of visual content in form of point clouds. Among other challenges, subjective and objective quality assessments of point clouds are still open problems. Most proposed subjective quality evaluation methodologies are variants or extensions of counter parts from conventional approaches such as those proposed in various ITU-R and ITU-T recommendations. A key issue with point cloud content is that of rendering and display devices which are thoroughly different from those in other modalities in addition to novel applications which depart from traditional display devices. In this paper, we propose a radically different approach to point cloud subjective quality assessment for point cloud by making use of augmented reality head mounted displays. Beside description of the approach, we show examples of implementation of the proposed methodology and draw conclusions regarding its advantages and drawbacks. Finally, the proposed approach is used in assessing the performance of widely used objective metrics to compute quality of point cloud contents when they undergo various types of distortions such as corruption by noise, simplification and compression.