# Geometry-Based Compression of Plenoptic Point Clouds

arXiv: https://arxiv.org/abs/2608.11273 · HTML: https://mlsanity.com/paper/2608.11273/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 26 references that are in the map.
- First posted on arXiv 11 Aug 2026.

## Builds on (most cited first, 1 of 1)

- [Video-based compression for plenoptic point clouds](https://mlsanity.com/paper/1911.01355/) (2019)

## Abstract (arXiv)

Plenoptic point clouds (PPC) are novel data structures that represent the light from different viewing directions in order to provide a higher degree of realism to regular point clouds. This is achieved by associating each point to multiple colors instead of a single one. Here, we present a method to efficiently compress the attributes of a PPC, consisting of a Karhunen-Lo`eve transform over the color attributes followed by multiple attribute coders with intra prediction capability. This compression scheme can be incorporated within the MPEG's geometry-based PCC (G-PCC) standard, using any of G-PCC's existing solutions for attribute coding. Compression performance assessment using PPCs of different spatial resolutions reveals competitive results in comparison to existing methods, such as RAHT-based or video-based PCC solutions. We believe our coder to be the new state of the art.