Abstract
3D point clouds are increasingly used in applications, such as 3D remapping, cultural heritage preservation, and virtual/augmented reality. Given their large data volume, efficient compression is crucial. The MPEG group has introduced two standards: Geometry-based Point Cloud Compression (G-PCC), for static and dynamic-acquired point clouds, and Video-based Point Cloud Compression (V-PCC), specifically for dynamic point clouds. Although both approaches achieve effective data reduction, their high computational complexity limits real-time use, especially on resource-constrained devices. This paper analyzes the computational cost and coding efficiency of G-PCC and V-PCC, identifying the most time-consuming steps. In G-PCC, the Octree-RAHT configuration offers the best trade-off between efficiency and encoding time, with recoloring alone accounting for up to 70%. In V-PCC, video encoding dominates, consuming about 92% of the total time. These findings lay the groundwork for future optimizations to reduce the complexity of more efficient implementations.
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The findings of this study are based entirely on publicly available software and analytical tools. All results generated during the research are presented within the manuscript in the form of tables and figures.
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Acknowledgements
This work was supported by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES), National Council for Scientific and Technological Development - CNPq and Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul - FAPERGS, Termo de Outorga: 23/2551-0000182-9.
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Santos, C., Rehbein, G., Costa, E. et al. Efficiency and complexity analysis of video-based and geometry-based point cloud encoders. J Real-Time Image Proc 22, 114 (2025). https://doi.org/10.1007/s11554-025-01689-9
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DOI: https://doi.org/10.1007/s11554-025-01689-9