Point Cloud Coding Solutions, Subjective Assessment and Objective Measures: A Case Study

Abstract

This paper presents a summary of recent progress in compression, subjective assessment and objective quality measures of point cloud representations of three dimensional visual information. Different existing point cloud datasets, as well as discusses the protocols that have been proposed to evaluate the subjective quality of point cloud data. Several geometry and attribute point cloud data objective quality measures are also presented and described. A case study on the evaluation of subjective quality of point clouds in two laboratories is presented. Six original point clouds degraded with G-PCC and V-PCC point cloud compression and five degradation levels were subjectively evaluated, showing high inter-laboratory correlation. Furthermore, performance of several geometry-based objective quality measures applied to the same data are described, concluding that the highest correlation with subjective scores is obtained using point-to-plane measures. Finally, several current challenges and future research directions on point clouds compression and quality evaluation are discussed.