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arXiv · 2608.11273

Geometry-Based Compression of Plenoptic Point Clouds

Davi R. Freitas·Gustavo L. Sandri·Ricardo L. de Queiroz
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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-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.

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Davi R. Freitas, Gustavo L. Sandri, Ricardo L. de Queiroz. 2026-08-11. Geometry-Based Compression of Plenoptic Point Clouds. https://doi.org/10.1109/mmsp55362.2022.9949107

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