# Occupancy-map-based rate distortion optimization for video-based point cloud compression

## TL;DR

This paper introduces a rate optimization method for video-based point cloud compression that reduces bitrate by ignoring unoccupied pixels during optimization, improving efficiency.

## Contribution

It proposes a novel rate distortion optimization approach that considers only occupied pixels, leading to significant bitrate savings in point cloud compression.

## Key findings

- Achieves 11.9% bitrate savings for geometry
- Achieves 15.4% bitrate savings for attributes
- Applicable to both geometry and attribute frames

## Abstract

The state-of-the-art video-based point cloud compression scheme projects the 3D point cloud to 2D patch by patch and organizes the patches into frames to compress them using the efficient video compression scheme. Such a scheme shows a good trade-off between the number of points projected and the video continuity to utilize the video compression scheme. However, some unoccupied pixels between different patches are compressed using almost the same quality with the occupied pixels, which will lead to the waste of lots of bits since the unoccupied pixels are useless for the reconstructed point cloud. In this paper, we propose to consider only the rate instead of the rate distortion cost for the unoccupied pixels during the rate distortion optimization process. The proposed scheme can be applied to both the geometry and attribute frames. The experimental results show that the proposed algorithm can achieve an average of 11.9% and 15.4% bitrate savings for the geometry and attribute, respectively.