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Reconstrucción virtual tridimensional de entornos urbanos complejos

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Reconstrucción virtual tridimensional de entornos urbanos complejos

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dc.contributor.author García-Moreno, A. es_ES
dc.contributor.author González-Barbosa, J. es_ES
dc.date.accessioned 2020-03-04T10:20:44Z
dc.date.available 2020-03-04T10:20:44Z
dc.date.issued 2020-01-01
dc.identifier.issn 1697-7912
dc.identifier.uri http://hdl.handle.net/10251/138325
dc.description.abstract [ES] Este trabajo presenta una metodología para la generación de modelos tridimensionales de entornos urbanos. Se utiliza una plataforma terrestre multi-sensores compuesta por un LIDAR, una cámara esférica, GPS y otros sistemas inerciales. Los datos de los sensores están sincronizados con el sistema de navegación y georrefenciados. La metodología de digitalizaciónn se centra en 3 procesos principales. (1) La reconstrucción tridimensional, en el cual se elimina el ruido en los datos 3D y se disminuye la distorsión en las imágenes. Posteriormente se construye una imagen panorámica. (2) La texturización, se describe a detalle el algoritmo para asegurar la menor incertidumbre en el proceso de extracción de color. (3) La generación de mallas, se describe el proceso de mallado basado en octree’s, desde la generación de la semilla, el teselado, así como la eliminación de huecos en las mallas. Por último, se realiza una evaluación cuantitativa de la propuesta y se compara con otros enfoques existen es_ES
dc.description.abstract [EN] This paper presents a methodology for the generation of three-dimensional models of urban environments. A multi-sensor terrestrial platform composed of a LIDAR, a spherical camera, GPS and IMU systems is used. The data of the sensors are synchronized with the navigation system and georeferenced. The digitalization methodology is focused on 3 main processes. (1) The three-dimensional reconstruction, in which the noise in the 3D data is eliminated and the distortion in the images is reduced. Later, a panoramic image is built. (2) Texturing, the algorithm is described in detail to ensure the least uncertainty in this color extraction process. (3) Mesh generation, the meshing process based on octree’s is described, from the generation of the seed, the tessellation, as well as the elimination of gaps in the meshes. Finally, a quantitative evaluation of our proposal is made and compared with other existing approaches in the state-of-the-art. The results obtained are discussed in detail. es_ES
dc.language Español es_ES
dc.publisher Universitat Politècnica de València es_ES
dc.relation.ispartof Revista Iberoamericana de Automática e Informática industrial es_ES
dc.rights Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) es_ES
dc.subject 3D reconstruction es_ES
dc.subject Texturing es_ES
dc.subject Meshing es_ES
dc.subject LIDAR es_ES
dc.subject Reconstrucción 3D es_ES
dc.subject Texturizado es_ES
dc.subject Mallado es_ES
dc.title Reconstrucción virtual tridimensional de entornos urbanos complejos es_ES
dc.title.alternative Virtual 3D reconstruction of complex urban environments es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.4995/riai.2019.11203
dc.rights.accessRights Abierto es_ES
dc.description.bibliographicCitation García-Moreno, A.; González-Barbosa, J. (2020). Reconstrucción virtual tridimensional de entornos urbanos complejos. Revista Iberoamericana de Automática e Informática industrial. 17(1):22-33. https://doi.org/10.4995/riai.2019.11203 es_ES
dc.description.accrualMethod OJS es_ES
dc.relation.publisherversion https://doi.org/10.4995/riai.2019.11203 es_ES
dc.description.upvformatpinicio 22 es_ES
dc.description.upvformatpfin 33 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 17 es_ES
dc.description.issue 1 es_ES
dc.identifier.eissn 1697-7920
dc.relation.pasarela OJS\11203 es_ES
dc.description.references Bernard O Abayowa, Alper Yilmaz, and Russell C Hardie. Automatic registration of optical aerial imagery to a lidar point cloud for generation of city models. ISPRS Journal of Photogrammetry and Remote Sensing, 106:68-81, 2015. https://doi.org/10.1016/j.isprsjprs.2015.05.006 es_ES
dc.description.references Gerardo Atanacio-Jiménez, José-Joel González-Barbosa, Juan B Hurtado-Ramos, Francisco J Ornelas-Rodríguez, Hugo Jiménez-Hernández, Teresa García-Ramirez, and Ricardo González-Barbosa. Lidar velodyne hdl-64e calibration using pattern planes. International Journal on Advanced Robotics Systems, 8(5):70-82, 2011. https://doi.org/10.5772/50900 es_ES
dc.description.references Matthew Brown, Richard Szeliski, and Simon Winder. Multi-image matching using multi-scale oriented patches. In Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on, volume 1, pages 510-517. IEEE, 2005. es_ES
dc.description.references Jonathan C Carr, Richard K Beatson, Jon B Cherrie, Tim J Mitchell, W Richard Fright, Bruce C McCallum, and Tim R Evans. Reconstruction and representation of 3d objects with radial basis functions. In Proceedings of the 28th annual conference on Computer graphics and interactive techniques, pages 67-76. ACM, 2001. es_ES
dc.description.references Ke Chen, Weisheng Lu, Fan Xue, Pingbo Tang, and Ling Hin Li. Automatic building information model reconstruction in high-density urban areas: Augmenting multi-source data with architectural knowledge. Automation in Construction, 93:22-34, 2018. https://doi.org/10.1016/j.autcon.2018.05.009 es_ES
dc.description.references Tamal K Dey and Samrat Goswami. Provable surface reconstruction from noisy samples. In Proceedings of the twentieth annual symposium on Computational geometry, pages 330-339. ACM, 2004. es_ES
dc.description.references Luca Di Angelo, Paolo Di Stefano, and Luigi Giaccari. A new mesh-growing algorithm for fast surface reconstruction. Computer-Aided Design, 43(6): 639-650, 2011. https://doi.org/10.1016/j.cad.2011.02.012 es_ES
dc.description.references Julie Digne. An analysis and implementation of a parallel ball pivoting algorithm. Image Processing On Line, 4:149-168, 2014. https://doi.org/10.5201/ipol.2014.81 es_ES
dc.description.references Damien Garcia. Robust smoothing of gridded data in one and higher dimensions with missing values. Computational statistics & data analysis, 54(4):1167-1178, 2010. https://doi.org/10.1016/j.csda.2009.09.020 es_ES
dc.description.references Angel-Iván García-Moreno, José-Joel Gonzalez-Barbosa, Francisco-Javier Ornelas-Rodriguez, Juan B Hurtado-Ramos, and Marco-Neri Primo-Fuentes. Lidar and panoramic camera extrinsic calibration approach using a pattern plane. In Pattern Recognition. Springer, 2013. https://doi.org/10.1007/978-3-642-38989-4_11 es_ES
dc.description.references Angel-Iván García-Moreno, Denis-Eduardo Hernandez-García, José-Joel Gonzalez-Barbosa, Alfonso Ramírez-Pedraza, Juan B Hurtado-Ramos, and Francisco-Javier Ornelas-Rodriguez. Error propagation and uncertainty analysis between 3d laser scanner and camera. Robotics and Autonomous Systems, 62(6):782-793, 2014. https://doi.org/10.1016/j.robot.2014.02.004 es_ES
dc.description.references Angel-Iván García-Moreno, José-Joel González-Barbosa, Alfonso Ramírez-Pedraza, Juan B Hurtado-Ramos, and Francisco-Javier Ornelas-Rodriguez. Accurate evaluation of sensitivity for calibration between a lidar and a panoramic camera used for remote sensing. Journal of Applied Remote Sensing, 10(2):024002-024002, 2016. https://doi.org/10.1117/1.JRS.10.024002 es_ES
dc.description.references Jianwei Guo, Dong-Ming Yan, Li Chen, Xiaopeng Zhang, Oliver Deussen, and Peter Wonka. Tetrahedral meshing via maximal poisson-disk sampling. Computer Aided Geometric Design, 43:186-199, 2016. https://doi.org/10.1016/j.cagd.2016.02.004 es_ES
dc.description.references Rostam Affendi Hamzah, A Fauzan Kadmin, M Saad Hamid, S Fakhar A Ghani, and Haidi Ibrahim. Improvement of stereo matching algorithm for 3d surface reconstruction. Signal Processing: Image Communication, 65:165-172, 2018. https://doi.org/10.1016/j.image.2018.04.001 es_ES
dc.description.references Chris Harris. Geometry from visual motion. In Active vision, pages 263-284. MIT Press, 1993. es_ES
dc.description.references C. Hatger and C. Brenner. Extraction of road geometry parameters from laser scanning and existing databases. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 34(3/W13):225-230, 2003. es_ES
dc.description.references Dorota Iwaszczuk and Uwe Stilla. Camera pose refinement by matching uncertain 3d building models with thermal infrared image sequences for high quality texture extraction. ISPRS Journal of Photogrammetry and Remote Sensing, 132:33-47, 2017. https://doi.org/10.1016/j.isprsjprs.2017.08.006 es_ES
dc.description.references Hansung Kim and Adrian Hilton. Block world reconstruction from spherical stereo image pairs. Computer Vision and Image Understanding, 139:104-121, 2015. https://doi.org/10.1016/j.cviu.2015.04.001 es_ES
dc.description.references Eyal Kushilevitz, Rafail Ostrovsky, and Yuval Rabani. Efficient search for approximate nearest neighbor in high dimensional spaces. SIAM Journal on Computing, 30(2):457-474, 2000. https://doi.org/10.1137/S0097539798347177 es_ES
dc.description.references Maxime Lhuillier. Surface reconstruction from a sparse point cloud by enforcing visibility consistency and topology constraints. Computer Vision and Image Understanding, 175:52-71, 2018. https://doi.org/10.1016/j.cviu.2018.09.007 es_ES
dc.description.references Lingyun Liu and Ioannis Stamos. A systematic approach for 2d-image to 3drange registration in urban environments. Computer Vision and Image Understanding, 116(1):25-37, 2012. https://doi.org/10.1016/j.cviu.2011.07.009 es_ES
dc.description.references Jules Morel, Alexandra Bac, and Cédric Véga. Surface reconstruction of incomplete datasets: A novel poisson surface approach based on csrbf. Computers & Graphics, 74:44-55, 2018. https://doi.org/10.1016/j.cag.2018.05.004 es_ES
dc.description.references Gaurav Pandey, James R McBride, and Ryan M Eustice. Ford campus vision and lidar data set. The International Journal of Robotics Research, 30(13): 1543-1552, 2011. https://doi.org/10.1177/0278364911400640 es_ES
dc.description.references Gaurav Pandey, James R McBride, Silvio Savarese, and Ryan M Eustice. Automatic extrinsic calibration of vision and lidar by maximizing mutual information. Journal of Field Robotics, 2014. https://doi.org/10.1002/rob.21542 es_ES
dc.description.references Yun Shi, Shunping Ji, Xiaowei Shao, Peng Yang, Wenbin Wu, Zhongchao Shi, and Ryosuke Shibasaki. Fusion of a panoramic camera and 2d laser scanner data for constrained bundle adjustment in gps-denied environments. Image and Vision Computing, 40:28-37, 2015. https://doi.org/10.1016/j.imavis.2015.06.002 es_ES
dc.description.references Miao Wang and Yi-Hsing Tseng. Automatic segmentation of lidar data into coplanar point clusters using an octree-based split-and-merge algorithm. Photogrammetric Engineering & Remote Sensing, 76(4):407-420, 2010. https://doi.org/10.14358/PERS.76.4.407 es_ES
dc.description.references Ruisheng Wang, Jeff Bach, Jane Macfarlane, and Frank P Ferrie. A new upsampling method for mobile lidar data. In Applications of Computer Vision (WACV), 2012 IEEE Workshop on, pages 17-24. IEEE, 2012. https://doi.org/10.1109/WACV.2012.6162998 es_ES
dc.description.references Bin Wu, Bailang Yu, Qiusheng Wu, Shenjun Yao, Feng Zhao, Weiqing Mao, and Jianping Wu. A graph-based approach for 3d building model reconstruction from airborne lidar point clouds. Remote Sensing, 9(1):92, 2017. https://doi.org/10.3390/rs9010092 es_ES
dc.description.references Lin Yang, Yehua Sheng, and Bo Wang. 3d reconstruction of building façade with fused data of terrestrial lidar data and optical image. Optik-International Journal for Light and Electron Optics, 127(4):2165-2168, 2016. https://doi.org/10.1016/j.ijleo.2015.11.147 es_ES
dc.description.references Michael Ying Yang, Yanpeng Cao, and John McDonald. Fusion of camera images and laser scans for wide baseline 3d scene alignment in urban environments. ISPRS Journal of Photogrammetry and Remote Sensing, 66(6): S52-S61, 2011. https://doi.org/10.1016/j.isprsjprs.2011.09.004 es_ES
dc.description.references Cheng Yi, Yuan Zhang, Qiaoyun Wu, Yabin Xu, Oussama Remil, Mingqiang Wei, and JunWang. Urban building reconstruction from raw lidar point data. Computer-Aided Design, 93:1-14, 2017. https://doi.org/10.1016/j.cad.2017.07.005 es_ES
dc.description.references Fanyang Zeng and Ruofei Zhong. The algorithm to generate color point-cloud with the registration between panoramic image and laser point-cloud. In IOP Conference Series: Earth and Environmental Science, volume 17, page 012160. IOP Publishing, 2014. https://doi.org/10.1088/1755-1315/17/1/012160 es_ES
dc.description.references SM Iman Zolanvari, Debra F Laefer, and Atteyeh S Natanzi. Three-dimensional building fac¸ade segmentation and opening area detection from point clouds. ISPRS journal of photogrammetry and remote sensing, 143:134-149, 2018. https://doi.org/10.1016/j.isprsjprs.2018.04.004 es_ES


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