Video-based compression for plenoptic point clouds

Abstract

The plenoptic point cloud that has multiple colors from various directions, is a more complete representation than the general point cloud that usually has only one color. It is more realistic but also brings a larger volume of data that needs to be compressed efficiently. The state-of-the-art method to compress the plenoptic point cloud is an extension of the region-based adaptive hierarchical transform (RAHT). As far as we can see, in addition to RAHT, the video-based point cloud compression (V-PCC) is also an efficient point cloud compression method. However, to the best of our knowledge, no works have used a videobased solution to compress the plenoptic point cloud yet. In this paper, we first extend the V-PCC to support the plenoptic point cloud compression by generating multiple attribute videos. Then based on the observation that these videos from multiple views have very high correlations, we propose encoding them using multiview high efficiency video coding. We further propose a block-based padding method that unifies the unoccupied attribute pixels from different views to reduce their bit cost. The proposed algorithms are implemented in the V-PCC reference software. The experimental results show that the proposed algorithms can bring significant bitrate savings compared with the state-of-the-art method for plenoptic point cloud compression.

Improved video-based point cloud compression via segmentation

“…The first test models to compress point clouds were developed in 2017, and the available software for Category 2 was named TMC2, and for Categories 1 and 3, TMC13. MPEG approved the most recent standardizations, G-PCC and V-PCC, in 2020 and early 2021 23,24 ; however, there are certain limitations for both, demonstrating that there is still an opportunity for future advancement of current technology [25][26][27] . V-PCC coding relies on transforming 3D data to 2D data to take advantage of the existing video coding and being able to compress 3D data using 2D video coding.…”