UDC 528.74
CSCSTI 36.23
The article considers the possibility of integrating outdoor and indoor threedimensional models of buildings to solve various problems, including information modeling and the creation of “digital twins”. An analytical review of methods for creating three-dimensional models of objects and territories is provided. The paper proposes a technological scheme for the main stages of building a three-dimensional model of terrain objects based on unmanned aerial vehicle photography, groundbased stereo photography of the facade and indoor model. A mathematical apparatus for combining two three-dimensional models made in different coordinate systems into a single 3D model is described. The article presents results of photogrammetric processing of aerial stereo photography, ground-based photography of building facades with a smartphone camera (build of a base model), and photography of the interior space of a building (indoor model) with a Sony Alpha ILCE-6000 camera. The indoor model can be combined with the base model using reference points measured with a total station. Combined 3D model according to the presented methodology can be used in carrying out restoration work, tasks of “seamless” navigation, and tasks of civil defense and emergency situations.
three-dimensional modeling, stereophotogrammetric method, unmanned aerial vehicle, ground-based stereo photography of facades, indoor 3D model, photogrammetric processing
1. Altuntas C. Three-Dimensional Digitization of Environments and Buildings for Smart City Applications // The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 2021. Vol. XLVI-4/W5-2021. P. 65–71. DOIhttps://doi.org/10.5194/isprs-archives-XLVI-4-W5-2021-65-2021. https://doi.org/10.5194/isprs-archives-XLVI-4-W5-2021-65-2021
2. Păulescu A.A., Ştefan M.E. 3D Modeling of Buildings Using Drones // Journal of Young Scientist. 2019. Vol. 7. P. 179–182.
3. Cera V., Campi M. Evaluating the Potential of Imaging Rover for Automatic Point Cloud Generation // The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 2017. Vol. XLII-2/W3. P. 147–154. DOIhttps://doi.org/10.5194/isprs-archives-XLII-2-W3-147-2017. https://doi.org/10.5194/isprs-archives-XLII-2-W3-147-2017
4. Fedorovskiy A.A. Osobennosti primeneniya metodiki nazemnoy stereofotogrammetricheskoy s'emki s pryamoy prostranstvennoy privyazkoy dlya trehmernogo modelirovaniya ob'ektov mestnosti // Izvestiya vuzov «Geodeziya i aerofotos'emka». 2022. T. 66, № 5. S. 73–86. DOIhttps://doi.org/10.30533/0536-101H-2022-66-5-73-86. https://www.miigaik.ru/journal/archive/2022/2022_66_5_RU/Geodesy_2022_66_5_RU_Fedorovskij.pdf?ysclid=mifquobzyy448367043
5. Abdulmajeed W.R., Mansoor R.Z. Implementing Kinect Sensor for Building 3D Maps of Indoor Environments // International Journal of Computer Applications. 2014. Vol. 86. No. 8. P. 18–22. DOIhttps://doi.org/10.5120/15005-3182. https://www.researchgate.net/profile/Wael-Abdulmajeed/publication/261721099_Implementing_Kinect_Sensor_for_Building_3D_Maps_of_Indoor_Environments/links/0f31752d7a88426885000000/Implementing-Kinect-Sensor-for-Building-3D-Maps-of-Indoor-Environments.pdf
6. Jóźków G., Toth C., Koppanyi Z., et al. Combined Matching of 2D and 3D Kinect™ Data to Support Indoor Mapping and Navigation // ASPRS 2014 Annual Conference. Louisville, Kentucky, USA, 23–28 March 2014. New York: Curran Associates, 2014. P. 164–174.
7. Henry P., Krainin M., Herbst E., et al. RGB-D mapping: Using Kinect-Style Depth Cameras for Dense 3D Modeling of Indoor Environments // The International Journal of Robotics Research. 2012. Vol. 31. No. 5. P. 647–663. DOIhttps://doi.org/10.1177/0278364911434148. https://doi.org/10.1177/0278364911434148
8. Altyncev M.A., Geraschenko G.D. Issledovanie tochnosti trehmernogo modelirovaniya po dannym s'emki s pomosch'yu nazemnogo lazernogo skanera Geomax Zoom 300 // Sbornik materialov XVIII Mezhdunarodnogo nauchnogo kongressa «Interekspo GEO-Sibir'», 18–20 maya 2022 g.: v 8 t. Novosibirsk: SGUGiT, 2022. T. 1. S. 76–85. DOIhttps://doi.org/10.33764/2618-981X-2022-1-76-85. https://sgugit.ru/upload/geosibir/sborniki/2022/tom-1/076-085.pdf?ysclid=mifrey88nw79398744
9. Skrypicyna T.N., Vorotilov A.G., Kochneva D.A. i dr. Osobennosti s'emki i metodika modelirovaniya chastichno razrushennyh arhitekturnyh ob'ektov po fotogrammetricheskim dannym // Materialy Mezhdunarodnoy konferencii «InterKarto. InterGIS». M.: Geograficheskiy fakul'tet MGU, 2024. T. 30, ch. 1. S. 556–567. DOIhttps://doi.org/10.35595/2414-9179-2024-1-30-556-567. https://doi.org/10.35595/2414-9179-2024-1-30-556-567
10. Molokov P.V., Scherbakov V.M. Sozdanie trehmernyh modeley ob'ektov istoriko-kul'turnogo naslediya s ispol'zovaniem nazemnogo lazernogo skanirovaniya i aerofotos'emki // Prostranstvennye dannye: nauka i tehnologii. 2024. T. 15, № 1. S. 46–61. DOIhttps://doi.org/10.30533/scidata-2024-15-09. https://www.elibrary.ru/item.asp?id=75132681
11. Shestopalova O.L., Shestopalov R.P. Ob integracii BIM-tehnologii informacionnogo modelirovaniya zdaniy s metodami fotogrammetrii pri postroenii cifrovyh modeley ob'ektov v arhitekturno-stroitel'noy otrasli // Izvestiya Tul'skogo gosudarstvennogo universiteta. Tehnicheskie nauki. 2022. № 8. S. 138–143. DOIhttps://doi.org/10.24412/2071-6168-2022-8-138-144. https://cyberleninka.ru/article/n/ob-integratsii-bim-tehnologii-informatsionnogo-modelirovaniya-zdaniy-s-metodami-fotogrammetrii-pri-postroenii-tsifrovyh-modeley?ysclid=mift9ryyrk652011204
12. Altyncev M.A. Metodika integracii dannyh nazemnogo i vozdushnogo lazernogo skanirovaniya // Izvestiya vuzov «Geodeziya i aerofotos'emka». 2023. T. 67, № 1. S. 26–41. DOIhttps://doi.org/10.30533/GiA-2023-007. https://miigaik.ru/journal/archive/2023/2023_67_1_RU/GiA-2023-007.pdf
13. Billen R., Cutting-Decelle A.F., Marina O., et al. 3D City Models and Urban Information: Current Issues and Perspectives. European COST Action TU0801. Les Ulis: EDP Sciences, 2014. 118 p. DOIhttps://doi.org/10.1051/TU0801/201400001. https://www.researchgate.net/publication/260172519_3D_City_Models_and_urban_information_Current_issues_and_perspectives
14. Wei S., Liu C., Tang N., et al. Indoor and Outdoor Multi-Source 3D Data Fusion Method for Ancient Buildings // Journal of Measurements in Engineering. 2022. Vol. 10. No. 3. P. 117–139. DOIhttps://doi.org/10.21595/jme.2022.22710. https://www.extrica.com/article/22710
15. Claridades A.R.C., Lee J. Defining a Model for Integrating Indoor and Outdoor Network Data to Support Seamless Navigation Applications // ISPRS International Journal of Geo-Information. 2021. Vol. 10. No. 8. P. 565. DOIhttps://doi.org/10.3390/ijgi10080565. https://www.mdpi.com/2220-9964/10/8/565
16. Tashakkori H., Rajabifard A., Kalantari M. A New 3D Indoor/Outdoor Spatial Model for Indoor Emergency Response Facilitation // Building and Environment. 2015. Vol. 89. P. 170–182. DOIhttps://doi.org/10.1016/j.buildenv.2015.02.036. https://doi.org/10.1016/j.buildenv.2015.02.036
17. Cohen A., Schönberger J.L., Speciale P., et al. Indoor-Outdoor 3D Reconstruction Alignment // Lecture Notes in Computer Science. 2016. Vol. 9907. P. 285–300. DOIhttps://doi.org/10.1007/978-3-319-46487-9_18. https://doi.org/10.1007/978-3-319-46487-9_18
18. Koch T., Korner M., Fraundorfer F. Automatic Alignment of Indoor and Outdoor Building Models Using 3D Line Segments // Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops. Las Vegas, NV, USA, 26 June – 1 July 2016. Red Hook: Curran Associates, 2016. P. 10–18. DOIhttps://doi.org/10.1109/CVPRW.2016.91. https://ieeexplore.ieee.org/document/7789581
