Construction of 3D Indoor Topological Models Based on Improved Face Sorting
Indoor location-based services and applications need to obtain information about the indoor spatial layouts and topological relationships of indoor spaces. The 3D city modeling data standard CityGML describes the indoor geometric and semantic information of buildings, but the surfaces composing a vo...
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MDPI AG
2025-01-01
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| Series: | ISPRS International Journal of Geo-Information |
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| Online Access: | https://www.mdpi.com/2220-9964/14/1/27 |
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| author | Qun Sun Xinwu Zhan Pu Tang |
| author_facet | Qun Sun Xinwu Zhan Pu Tang |
| author_sort | Qun Sun |
| collection | DOAJ |
| description | Indoor location-based services and applications need to obtain information about the indoor spatial layouts and topological relationships of indoor spaces. The 3D city modeling data standard CityGML describes the indoor geometric and semantic information of buildings, but the surfaces composing a volume are discrete, leading to invalid volumes. Moreover, the topological adjacency relationships of adjacent indoor spaces have not yet been described, which makes it difficult to realize effective queries and analyses for indoor applications. In this paper, we present a 3D topological data model for indoor spaces that adopts five topological primitives, namely, node, edge, loop, face, and solid, to describe the topological relationships of indoor spaces. Then, by improving the existing face-sorting method according to vector products in 3D space, a method for constructing 3D topological relationships for indoor spaces is proposed, which successively constructs the topological hierarchical combination of volume and the topological adjacency relationships of adjacent volumes. The experimental results show that by using the improved face-sorting method proposed in this work, the relative positions of faces are directly determined to sort the faces set, which avoids relatively cumbersome calculations and improves the efficiency of constructing 3D topological relationships for indoor spaces. |
| format | Article |
| id | doaj-art-ca0d07f09eb641f8a6fb8374cd6fbb5f |
| institution | Kabale University |
| issn | 2220-9964 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | ISPRS International Journal of Geo-Information |
| spelling | doaj-art-ca0d07f09eb641f8a6fb8374cd6fbb5f2025-01-24T13:35:01ZengMDPI AGISPRS International Journal of Geo-Information2220-99642025-01-011412710.3390/ijgi14010027Construction of 3D Indoor Topological Models Based on Improved Face SortingQun Sun0Xinwu Zhan1Pu Tang2School of Hydraulic Engineering, Nanchang Institute of Technology, Nanchang 330099, ChinaSchool of Hydraulic Engineering, Nanchang Institute of Technology, Nanchang 330099, ChinaSchool of Hydraulic Engineering, Nanchang Institute of Technology, Nanchang 330099, ChinaIndoor location-based services and applications need to obtain information about the indoor spatial layouts and topological relationships of indoor spaces. The 3D city modeling data standard CityGML describes the indoor geometric and semantic information of buildings, but the surfaces composing a volume are discrete, leading to invalid volumes. Moreover, the topological adjacency relationships of adjacent indoor spaces have not yet been described, which makes it difficult to realize effective queries and analyses for indoor applications. In this paper, we present a 3D topological data model for indoor spaces that adopts five topological primitives, namely, node, edge, loop, face, and solid, to describe the topological relationships of indoor spaces. Then, by improving the existing face-sorting method according to vector products in 3D space, a method for constructing 3D topological relationships for indoor spaces is proposed, which successively constructs the topological hierarchical combination of volume and the topological adjacency relationships of adjacent volumes. The experimental results show that by using the improved face-sorting method proposed in this work, the relative positions of faces are directly determined to sort the faces set, which avoids relatively cumbersome calculations and improves the efficiency of constructing 3D topological relationships for indoor spaces.https://www.mdpi.com/2220-9964/14/1/27indoor topological modelface sortingvector productCityGML3D GIS |
| spellingShingle | Qun Sun Xinwu Zhan Pu Tang Construction of 3D Indoor Topological Models Based on Improved Face Sorting ISPRS International Journal of Geo-Information indoor topological model face sorting vector product CityGML 3D GIS |
| title | Construction of 3D Indoor Topological Models Based on Improved Face Sorting |
| title_full | Construction of 3D Indoor Topological Models Based on Improved Face Sorting |
| title_fullStr | Construction of 3D Indoor Topological Models Based on Improved Face Sorting |
| title_full_unstemmed | Construction of 3D Indoor Topological Models Based on Improved Face Sorting |
| title_short | Construction of 3D Indoor Topological Models Based on Improved Face Sorting |
| title_sort | construction of 3d indoor topological models based on improved face sorting |
| topic | indoor topological model face sorting vector product CityGML 3D GIS |
| url | https://www.mdpi.com/2220-9964/14/1/27 |
| work_keys_str_mv | AT qunsun constructionof3dindoortopologicalmodelsbasedonimprovedfacesorting AT xinwuzhan constructionof3dindoortopologicalmodelsbasedonimprovedfacesorting AT putang constructionof3dindoortopologicalmodelsbasedonimprovedfacesorting |