Visual Quality of Compressed Mesh and Point Cloud Sequences
Keming Cao, Yi Xu, Pamela C. Cosman
Abstract
With the development of immersive video, the delivery and storage of 3D content have become important research areas. While compression methods for meshes and point clouds, the two main representations for 3D content, are actively studied, there are few studies of their perceptual compression quality and none that consider observation distance. In this paper, we study the perceptual quality of compressed 3D sequences, for both point cloud compression and mesh-based compression. We explore the impact of bit rate and observation distance on perceptual quality. Evaluation of perceptual quality is carried out both by collecting viewer opinion scores of the compressed sequences separately, and with a side-by-side comparison. A functional model for mesh and point cloud compression quality is estimated to predict Mean Opinion Score (MOS) which yields high Pearson correlation and rank correlation scores with measured MOS.