Extracting Regular Building Footprints Using Projection Histogram Method from UAV-Based 3D Models
Extracting building outlines from 3D models poses significant challenges stemming from the intricate diversity of structures and the complexity of urban scenes. Current techniques heavily rely on human expertise and involve repetitive, labor-intensive manual operations. To address these limitations,...
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2024-12-01
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| Series: | ISPRS International Journal of Geo-Information |
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| author | Yaoyao Ren Xing Li Fangyuqing Jin Chunmei Li Wei Liu Erzhu Li Lianpeng Zhang |
| author_facet | Yaoyao Ren Xing Li Fangyuqing Jin Chunmei Li Wei Liu Erzhu Li Lianpeng Zhang |
| author_sort | Yaoyao Ren |
| collection | DOAJ |
| description | Extracting building outlines from 3D models poses significant challenges stemming from the intricate diversity of structures and the complexity of urban scenes. Current techniques heavily rely on human expertise and involve repetitive, labor-intensive manual operations. To address these limitations, this paper presents an innovative automatic technique for accurately extracting building footprints, particularly those with gable and hip roofs, directly from 3D data. Our methodology encompasses several key steps: firstly, we construct a triangulated irregular network (TIN) to capture the intricate geometry of the buildings. Subsequently, we employ 2D indexing and counting grids for efficient data processing and utilize a sophisticated connected component labeling algorithm to precisely identify the extents of the roofs. A single seed point is manually specified to initiate the process, from which we select the triangular facets representing the outer walls of the buildings. Utilizing the projection histogram method, these facets are grouped and processed to extract regular building footprints. Extensive experiments conducted on datasets from Nanjing and Wuhan demonstrate the remarkable accuracy of our approach. With mean intersection over union (mIOU) values of 99.2% and 99.4%, respectively, and F1 scores of 94.3% and 96.7%, our method proves to be both effective and robust in mapping building footprints from 3D real-scene data. This work represents a significant advancement in automating the extraction of building footprints from complex 3D scenes, with potential applications in urban planning, disaster response, and environmental monitoring. |
| format | Article |
| id | doaj-art-a51c99dfd600410eb298053ff8e3a447 |
| institution | Kabale University |
| issn | 2220-9964 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
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| series | ISPRS International Journal of Geo-Information |
| spelling | doaj-art-a51c99dfd600410eb298053ff8e3a4472025-01-24T13:34:57ZengMDPI AGISPRS International Journal of Geo-Information2220-99642024-12-01141610.3390/ijgi14010006Extracting Regular Building Footprints Using Projection Histogram Method from UAV-Based 3D ModelsYaoyao Ren0Xing Li1Fangyuqing Jin2Chunmei Li3Wei Liu4Erzhu Li5Lianpeng Zhang6School of Geography, Geomatics and Planning, Jiangsu Normal University, Xuzhou 221116, ChinaSchool of Geography, Geomatics and Planning, Jiangsu Normal University, Xuzhou 221116, ChinaSchool of Geography, Geomatics and Planning, Jiangsu Normal University, Xuzhou 221116, ChinaSchool of Geography, Geomatics and Planning, Jiangsu Normal University, Xuzhou 221116, ChinaSchool of Geography, Geomatics and Planning, Jiangsu Normal University, Xuzhou 221116, ChinaSchool of Geography, Geomatics and Planning, Jiangsu Normal University, Xuzhou 221116, ChinaSchool of Geography, Geomatics and Planning, Jiangsu Normal University, Xuzhou 221116, ChinaExtracting building outlines from 3D models poses significant challenges stemming from the intricate diversity of structures and the complexity of urban scenes. Current techniques heavily rely on human expertise and involve repetitive, labor-intensive manual operations. To address these limitations, this paper presents an innovative automatic technique for accurately extracting building footprints, particularly those with gable and hip roofs, directly from 3D data. Our methodology encompasses several key steps: firstly, we construct a triangulated irregular network (TIN) to capture the intricate geometry of the buildings. Subsequently, we employ 2D indexing and counting grids for efficient data processing and utilize a sophisticated connected component labeling algorithm to precisely identify the extents of the roofs. A single seed point is manually specified to initiate the process, from which we select the triangular facets representing the outer walls of the buildings. Utilizing the projection histogram method, these facets are grouped and processed to extract regular building footprints. Extensive experiments conducted on datasets from Nanjing and Wuhan demonstrate the remarkable accuracy of our approach. With mean intersection over union (mIOU) values of 99.2% and 99.4%, respectively, and F1 scores of 94.3% and 96.7%, our method proves to be both effective and robust in mapping building footprints from 3D real-scene data. This work represents a significant advancement in automating the extraction of building footprints from complex 3D scenes, with potential applications in urban planning, disaster response, and environmental monitoring.https://www.mdpi.com/2220-9964/14/1/6building footprintsregularizationprojection histogramconnected component labeling3D real-scene |
| spellingShingle | Yaoyao Ren Xing Li Fangyuqing Jin Chunmei Li Wei Liu Erzhu Li Lianpeng Zhang Extracting Regular Building Footprints Using Projection Histogram Method from UAV-Based 3D Models ISPRS International Journal of Geo-Information building footprints regularization projection histogram connected component labeling 3D real-scene |
| title | Extracting Regular Building Footprints Using Projection Histogram Method from UAV-Based 3D Models |
| title_full | Extracting Regular Building Footprints Using Projection Histogram Method from UAV-Based 3D Models |
| title_fullStr | Extracting Regular Building Footprints Using Projection Histogram Method from UAV-Based 3D Models |
| title_full_unstemmed | Extracting Regular Building Footprints Using Projection Histogram Method from UAV-Based 3D Models |
| title_short | Extracting Regular Building Footprints Using Projection Histogram Method from UAV-Based 3D Models |
| title_sort | extracting regular building footprints using projection histogram method from uav based 3d models |
| topic | building footprints regularization projection histogram connected component labeling 3D real-scene |
| url | https://www.mdpi.com/2220-9964/14/1/6 |
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