3D Reconstruction of Geometries for Urban Areas Supported by Computer Vision or Procedural Generations

This work presents a numerical mesh generation method for 3D urban scenes that could be easily converted into any 3D format, different from most implementations which are limited to specific environments in their applicability. The building models have shaped roofs and faces with static colors, comb...

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Detalles Bibliográficos
Autores: Liu Xiao, Hanli, Hellín Asensio, Carlos Javier|||0000-0002-1576-5466, Tayebi Tayebi, Abdelhamid|||0000-0002-6216-257X, Delgado Hita, Carlos|||0000-0003-0981-6527, Gómez Pérez, Josefa|||0000-0003-0111-8898
Tipo de recurso: artículo
Fecha de publicación:2024
País:España
Institución:Universidad de Alcalá (UAH)
Repositorio:e_Buah Biblioteca Digital Universidad de Alcalá
Idioma:inglés
OAI Identifier:oai:ebuah.uah.es:10017/67794
Acceso en línea:http://hdl.handle.net/10017/67794
https://dx.doi.org/10.3390/math12213331
Access Level:acceso abierto
Palabra clave:3D city model
Spatial model
Static 3D reconstruction
Building information modeling
OpenStreetMap
Computer vision
Google Maps
Informática
Computer science
Descripción
Sumario:This work presents a numerical mesh generation method for 3D urban scenes that could be easily converted into any 3D format, different from most implementations which are limited to specific environments in their applicability. The building models have shaped roofs and faces with static colors, combining the buildings with a ground grid. The building generation uses geographic positions and shape names, which can be extracted from OpenStreetMap. Additional steps, like a computer vision method, can be integrated into the generation optionally to improve the quality of the model, although this is highly time-consuming. Its function is to classify unknown roof shapes from satellite images with adequate resolution. The generation can also use custom geographic information. This aspect was tested using information created by procedural processes. The method was validated by results generated for many realistic scenarios with multiple building entities, comparing the results between using computer vision and not. The generated models were attempted to be rendered under Graphics Library Transmission Format and Unity Engine. In future work, a polygon-covering algorithm needs to be completed to process the building footprints more effectively, and a solution is required for the missing height values in OpenStreetMap.