Research on simplification of 3D fine model based on UE5

Dongchao Sun

doi:10.1117/12.3007385

30 August 2023 Research on simplification of 3D fine model based on UE5

Dongchao Sun

Proceedings Volume 12797, Second International Conference on Geographic Information and Remote Sensing Technology (GIRST 2023); 127971B (2023) https://doi.org/10.1117/12.3007385
Event: 2nd International Conference on Geographic Information and Remote Sensing Technology (GIRST 2023), 2023, Qingdao, China

Abstract

The current large-scale visualization of 3D geographic scenes, such as real-life 3D and smart cities, requires a large number of fine models such as triangulation networks and patches. Conventional engines are difficult to load such large-scale 3D GIS data, and computers require extremely high memory and graphics memory to load the entire scene data, making it difficult for conventional computers to achieve. To solve this problem, this paper adopts the multi-resolution construction method of fine model, uses adaptive node division to improve the spatial data organization of the traditional octree fine model and the task stealing algorithm to improve the existing parallel divide and conquer merge algorithm to build a triangular network, and optimizes the edge collapse simplification algorithm based on improved QEM through multithreading during the model construction process before simplifying the triangular network, To ensure fast transmission in UE5 and efficient rendering on GPU.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Dongchao Sun "Research on simplification of 3D fine model based on UE5", Proc. SPIE 12797, Second International Conference on Geographic Information and Remote Sensing Technology (GIRST 2023), 127971B (30 August 2023); https://doi.org/10.1117/12.3007385

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