A framework for street view texture refinement of LoD2 building model using roughly posed terrestrial photos
UAV-based oblique photogrammetric 3D reconstruction is widely utilized for large-scale urban modeling, and shop signs on the reconstructed models serve as vital elements for visualization and various urban research. However, the texture quality, particularly at street level, is often influenced by l...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2025-08-01
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| Series: | International Journal of Digital Earth |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/17538947.2025.2483381 |
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| _version_ | 1849224302630535168 |
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| author | Yunlong Zheng Xianfeng Huang Liang Ge Mao Ye Wenxuan Liu Fan Zhang Hanyu Xiang Zepeng Hou |
| author_facet | Yunlong Zheng Xianfeng Huang Liang Ge Mao Ye Wenxuan Liu Fan Zhang Hanyu Xiang Zepeng Hou |
| author_sort | Yunlong Zheng |
| collection | DOAJ |
| description | UAV-based oblique photogrammetric 3D reconstruction is widely utilized for large-scale urban modeling, and shop signs on the reconstructed models serve as vital elements for visualization and various urban research. However, the texture quality, particularly at street level, is often influenced by low resolution and occlusion, resulting in blurred and illegible shop signs. This paper proposes a framework to refine street view shop sign textures on LoD2 building models generated by oblique photogrammetry. Using building models and roughly posed terrestrial photos as input, the framework employs ray-mesh intersection for coarse image-to-model alignment, and then applies a multi-scale point-area fused image matching strategy for precise texture refinement. While designed with a specific POS device, it can adapt to systems providing pose data of similar or even lower accuracy. Both visual and statistical results demonstrate the effectiveness of our approach in enhancing texture quality and overall visual fidelity. The dataset used in this research is available at this URL. |
| format | Article |
| id | doaj-art-81a8077c9b3c40ac866b2ac26f23242a |
| institution | Kabale University |
| issn | 1753-8947 1753-8955 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | International Journal of Digital Earth |
| spelling | doaj-art-81a8077c9b3c40ac866b2ac26f23242a2025-08-25T11:31:40ZengTaylor & Francis GroupInternational Journal of Digital Earth1753-89471753-89552025-08-0118110.1080/17538947.2025.2483381A framework for street view texture refinement of LoD2 building model using roughly posed terrestrial photosYunlong Zheng0Xianfeng Huang1Liang Ge2Mao Ye3Wenxuan Liu4Fan Zhang5Hanyu Xiang6Zepeng Hou7State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing, Wuhan University, Wuhan, People’s Republic of ChinaState Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing, Wuhan University, Wuhan, People’s Republic of ChinaTianjin Institute of Surveying and Mapping Company Limited, Tianjin, People’s Republic of ChinaState Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing, Wuhan University, Wuhan, People’s Republic of ChinaWuhan Daspatial Technology Co., Ltd., Wuhan, People’s Republic of ChinaState Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing, Wuhan University, Wuhan, People’s Republic of ChinaState Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing, Wuhan University, Wuhan, People’s Republic of ChinaState Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing, Wuhan University, Wuhan, People’s Republic of ChinaUAV-based oblique photogrammetric 3D reconstruction is widely utilized for large-scale urban modeling, and shop signs on the reconstructed models serve as vital elements for visualization and various urban research. However, the texture quality, particularly at street level, is often influenced by low resolution and occlusion, resulting in blurred and illegible shop signs. This paper proposes a framework to refine street view shop sign textures on LoD2 building models generated by oblique photogrammetry. Using building models and roughly posed terrestrial photos as input, the framework employs ray-mesh intersection for coarse image-to-model alignment, and then applies a multi-scale point-area fused image matching strategy for precise texture refinement. While designed with a specific POS device, it can adapt to systems providing pose data of similar or even lower accuracy. Both visual and statistical results demonstrate the effectiveness of our approach in enhancing texture quality and overall visual fidelity. The dataset used in this research is available at this URL.https://www.tandfonline.com/doi/10.1080/17538947.2025.24833813D city modelingUAV-based oblique photogrammetrymodel texture refinementray-mesh intersectionimage matchingaerial-ground integration |
| spellingShingle | Yunlong Zheng Xianfeng Huang Liang Ge Mao Ye Wenxuan Liu Fan Zhang Hanyu Xiang Zepeng Hou A framework for street view texture refinement of LoD2 building model using roughly posed terrestrial photos International Journal of Digital Earth 3D city modeling UAV-based oblique photogrammetry model texture refinement ray-mesh intersection image matching aerial-ground integration |
| title | A framework for street view texture refinement of LoD2 building model using roughly posed terrestrial photos |
| title_full | A framework for street view texture refinement of LoD2 building model using roughly posed terrestrial photos |
| title_fullStr | A framework for street view texture refinement of LoD2 building model using roughly posed terrestrial photos |
| title_full_unstemmed | A framework for street view texture refinement of LoD2 building model using roughly posed terrestrial photos |
| title_short | A framework for street view texture refinement of LoD2 building model using roughly posed terrestrial photos |
| title_sort | framework for street view texture refinement of lod2 building model using roughly posed terrestrial photos |
| topic | 3D city modeling UAV-based oblique photogrammetry model texture refinement ray-mesh intersection image matching aerial-ground integration |
| url | https://www.tandfonline.com/doi/10.1080/17538947.2025.2483381 |
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