As an important representation form of three-dimensional scenes, the point cloud contains rich geometry and attribute information. The video-based point cloud compression standard (V-PCC) divides and projects three-dimensional data directionally onto a two-dimensional plane. The generated geometric and attribute graphs contain occupied pixels obtained by projection and unoccupied pixels used for smooth filling. Among them, the non-occupied pixels have no practical effect on the reconstructed point cloud. However, in the process of encoding bitrate allocation, V-PCC still uses the original bitrate control method, resulting in insufficient bitrate utilization efficiency. To this end, this paper proposes a method for optimizing the unoccupied pixels of point cloud videos based on V-PCC and jointly controlling the coding rate of geometries and attribute graphs. For geometric graphs, this paper improves the allocation of bitrate weights based on whether the encoded blocks contain non-occupied pixels and the proportion of occupied pixels, and stops allocating bitrates to encoded blocks that are all non-occupied pixels. For the attribute graph, the input pixel improvement algorithm is designed by using the occupation map, and the invalid unoccupied pixel information is cavitation. Experiments show that under the All Intra configuration, compared with the original scheme, this method reduces the Geom.BD-GeomRate by an average of 15.67% and 16.68%, respectively, in the point-to-point D1 and point-to-face D2 metrics. The end-to-end BD-AttrRate is reduced by an average of 4.38%, 0.68%, and 1.74%, respectively. Overall, the average savings are 29.88%, 31.50%, 5.50%, 2.66%, and 3.34%, respectively, achieving bitrate optimization and effectively controlling encoding loss.
Wang et al. (Tue,) studied this question.