A 3D Reconstruction and Optimization Algorithm Based on GIM Model

At present, GIM models face problems in the field of 3D modeling, including the complex hierarchical architecture of the model, the incomplete model classification information, many imaging topology errors of the model, and the non-standardized phenomenon of attribute storage. These problems hinder...

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Bibliographic Details
Published in2024 IEEE 2nd International Conference on Power Science and Technology (ICPST) pp. 2152 - 2157
Main Authors Zhang, Yaping, Rong, Jingguo, Zhang, Zhuoqun, Zhang, Su, Wang, Fei
Format Conference Proceeding
LanguageEnglish
Published IEEE 09.05.2024
Subjects
3D reconstruction
Accuracy
Data models
Memory
Merging
optimization algorithm
power grid information model
Solid modeling
Three-dimensional displays
Visual effects
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Summary:At present, GIM models face problems in the field of 3D modeling, including the complex hierarchical architecture of the model, the incomplete model classification information, many imaging topology errors of the model, and the non-standardized phenomenon of attribute storage. These problems hinder the effective application and widespread dissemination of GIM models. This makes the fusion of GIM model and geographic information data has not yet reached the ideal state, which makes its digital application scope relatively limited. To solve the above problems, the 3D modeling and optimization method of power grid information model are studied deeply. Therefore, a data storage method based on B-tree structure is proposed, aiming to realize the unified storage of GIM data and the restoration of hierarchy structure. This not only standardizes the storage mode of attribute data, restores the complex hierarchical architecture of the model, but also facilitates the data exchange between different systems, and further promotes the application and development of GIM model. Moreover, because the pole-tower 3D model provided by GIM has some point accuracy problems in the original measurement, this study proposed an optimization algorithm based on adjacent point merging. It improves the accuracy and efficiency of the model data processing, and significantly enhances the visual effect of the model and provides a more solid and comprehensive technical support for the research and application of related fields.
DOI:10.1109/ICPST61417.2024.10602469