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Geometry-Based Compression of Plenoptic Point Clouds

2026-08-11 08:00:29
Davi R. Freitas, Gustavo L. Sandri, Ricardo L. de Queiroz
arXiv_CV
     
Abstract

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-Loève 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.

Abstract (translated)

URL

https://arxiv.org/abs/2608.11273

PDF

https://arxiv.org/pdf/2608.11273.pdf

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