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Vol. 32, No. 8(2), S&M2292

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Sensors and Materials, Volume 34, Number 1(3) (2022)
Copyright(C) MYU K.K.
pp. 277-287
S&M2810 Research Paper of Special Issue
https://doi.org/10.18494/SAM.2022.3563
Published in advance: December 13, 2021
Published: January 31, 2022

3D Scene Management Method Combined with Scene Graphs [PDF]

Xiang Wang, Tao Shen, Liang Huo, Congnan Guo, and Su Gao

(Received July 21, 2021; Accepted November 16, 2021)

Keywords: 3D scene management, adaptive quadtree, LOD, scene graph, hybrid index

The rendering of urban 3D scenes involves a large number of models, where the computer performance becomes a limitation. Arbitrarily putting all the models in a folder for storage significantly reduces the data processing efficiency when the models are called. There are also issues of storage redundancy and semantic fragmentation at the storage boundary. We propose a 3D scene management method based on an adaptive quadtree and scene graph (AQT-SG) that can solve the above problems. According to the spatial distribution characteristics of 3D scene data, this method adopts an adaptive quadtree for organizing complex 3D city scenes at the macro and meso scales, traversing the quadtree from bottom to top and calculating the geometric error at each level and in the middle. The node generates level of detail, builds a flexible multiscale 3D tile model, and uses scene graphs for the microscale organization and management of 3D scenes. We verified the proposed method with park data from a smart park management system. Large-scale complex 3D scene visualization and a comparison of the results of storage redundancy experiments verified that the data organization efficiency was optimized and the visual experience was improved by this method.

Corresponding author: Tao Shen, Liang Huo


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Cite this article
Xiang Wang, Tao Shen, Liang Huo, Congnan Guo, and Su Gao, 3D Scene Management Method Combined with Scene Graphs, Sens. Mater., Vol. 34, No. 1, 2022, p. 277-287.



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