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基于空间语义分区在网页浏览器上动态加载IFC模型。

Dynamically loading IFC models on a web browser based on spatial semantic partitioning.

作者信息

Lu Hong-Lei, Wu Jia-Xing, Liu Yu-Shen, Wang Wan-Qi

机构信息

School of Software, Tsinghua University, Beijing, 100084, China.

Beijing National Research Center for Information Science and Technology (BNRist), Beijing, 100084, China.

出版信息

Vis Comput Ind Biomed Art. 2019 Jun 3;2(1):4. doi: 10.1186/s42492-019-0011-z.

DOI:10.1186/s42492-019-0011-z
PMID:32240404
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7099568/
Abstract

Industry foundation classes (IFC) is an open and neutral data format specification for building information modeling (BIM) that plays a crucial role in facilitating interoperability. With increases in web-based BIM applications, there is an urgent need for fast loading large IFC models on a web browser. However, the task of fully loading large IFC models typically consumes a large amount of memory of a web browser or even crashes the browser, and this significantly limits further BIM applications. In order to address the issue, a method is proposed for dynamically loading IFC models based on spatial semantic partitioning (SSP). First, the spatial semantic structure of an input IFC model is partitioned via the extraction of story information and establishing a component space index table on the server. Subsequently, based on user interaction, only the model data that a user is interested in is transmitted, loaded, and displayed on the client. The presented method is implemented via Web Graphics Library, and this enables large IFC models to be fast loaded on the web browser without requiring any plug-ins. When compared with conventional methods that load all IFC model data for display purposes, the proposed method significantly reduces memory consumption in a web browser, thereby allowing the loading of large IFC models. When compared with the existing method of spatial partitioning for 3D data, the proposed SSP entirely uses semantic information in the IFC file itself, and thereby provides a better interactive experience for users.

摘要

工业基础类(IFC)是一种用于建筑信息模型(BIM)的开放且中立的数据格式规范,在促进互操作性方面发挥着关键作用。随着基于网络的BIM应用的增加,迫切需要在网络浏览器上快速加载大型IFC模型。然而,完全加载大型IFC模型的任务通常会消耗网络浏览器的大量内存,甚至导致浏览器崩溃,这严重限制了BIM的进一步应用。为了解决这个问题,提出了一种基于空间语义分区(SSP)动态加载IFC模型的方法。首先,通过提取楼层信息并在服务器上建立组件空间索引表,对输入的IFC模型的空间语义结构进行分区。随后,基于用户交互,仅将用户感兴趣的模型数据传输、加载并显示在客户端。所提出的方法通过Web图形库实现,这使得大型IFC模型能够在网络浏览器上快速加载,而无需任何插件。与为显示目的而加载所有IFC模型数据的传统方法相比,所提出的方法显著降低了网络浏览器中的内存消耗,从而允许加载大型IFC模型。与现有的3D数据空间分区方法相比,所提出的SSP完全使用IFC文件本身中的语义信息,从而为用户提供了更好的交互体验。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a125/7099568/77b24b0930ef/42492_2019_11_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a125/7099568/bf70b6479bd2/42492_2019_11_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a125/7099568/8780657faa83/42492_2019_11_Fig2_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a125/7099568/5bb11cd3b5af/42492_2019_11_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a125/7099568/9c03767cad1c/42492_2019_11_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a125/7099568/56216c25d343/42492_2019_11_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a125/7099568/5c01e4125f8c/42492_2019_11_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a125/7099568/f20fb07ef788/42492_2019_11_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a125/7099568/62a9c3d8c095/42492_2019_11_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a125/7099568/0bd87f8c7080/42492_2019_11_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a125/7099568/77b24b0930ef/42492_2019_11_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a125/7099568/bf70b6479bd2/42492_2019_11_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a125/7099568/8780657faa83/42492_2019_11_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a125/7099568/4bda16a29eab/42492_2019_11_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a125/7099568/5bb11cd3b5af/42492_2019_11_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a125/7099568/9c03767cad1c/42492_2019_11_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a125/7099568/56216c25d343/42492_2019_11_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a125/7099568/5c01e4125f8c/42492_2019_11_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a125/7099568/f20fb07ef788/42492_2019_11_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a125/7099568/62a9c3d8c095/42492_2019_11_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a125/7099568/0bd87f8c7080/42492_2019_11_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a125/7099568/77b24b0930ef/42492_2019_11_Fig11_HTML.jpg

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