S&M Young Researcher Paper Award 2020
Recipients: Ding Jiao, Zao Ni, Jiachou Wang, and Xinxin Li [Winner's comments]
Paper: High Fill Factor Array of Piezoelectric Micromachined
Ultrasonic Transducers with Large Quality Factor

S&M Young Researcher Paper Award 2021
Award Criteria
Notice of retraction
Vol. 32, No. 8(2), S&M2292

Print: ISSN 0914-4935
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Sensors and Materials
is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.

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3D Scene Management Method Combined with Scene Graphs

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 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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