{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T12:53:37Z","timestamp":1753880017822,"version":"3.41.2"},"reference-count":33,"publisher":"ASME International","issue":"4","license":[{"start":{"date-parts":[[2020,2,24]],"date-time":"2020-02-24T00:00:00Z","timestamp":1582502400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.asme.org\/publications-submissions\/publishing-information\/legal-policies"}],"content-domain":{"domain":["asmedigitalcollection.asme.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2020,8,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Three-dimensional urban reconstruction requires the combination of data from different sensors, such as cameras, inertial systems, GPS, and laser sensors. In this technical report, a complete system for the generation of textured volumetric global maps (deep vision) is presented. Our acquisition platform is terrestrial and moves through different urban environments digitizing them. The report is focused on describing the three main problems identified in this type of works. (1) The acquisition of three-dimensional data with high precision, (2) the extraction of the texture and its correlation with the 3D data, and (3) the generation of the surfaces that describe the components of the urban environment. It also describes the methods implemented to extrinsically calibrate the acquisition platform, as well as the methods developed to eliminate the radial and tangential image distortion; and the subsequent generation of a panoramic image. Procedures are developed for the sampling of 3D data and its smoothing. Subsequently, the process to generate textured global maps with a negligible uncertainty is developed and the results are presented. Finally, the process of surface generation and the post-process of eliminating certain holes\/occlusions in the meshes are reported. In each section, results obtained are shown. Using the methods presented here for geometric and photorealistic reconstruction of urban environments, high-quality 3D models are generated. The results achieved the following objectives: generate global textured models that preserve the geometry of the scanned scenes.<\/jats:p>","DOI":"10.1115\/1.4045172","type":"journal-article","created":{"date-parts":[[2019,10,14]],"date-time":"2019-10-14T17:50:51Z","timestamp":1571075451000},"update-policy":"https:\/\/doi.org\/10.1115\/crossmarkpolicy-asme","source":"Crossref","is-referenced-by-count":1,"title":["Dynamic Multi-Sensor Platform for Efficient Three-Dimensional-Digitalization of Cities"],"prefix":"10.1115","volume":"20","author":[{"given":"Angel-Iv\u00e1n","family":"Garc\u00eda-Moreno","sequence":"first","affiliation":[{"name":"Center for Engineering and Industrial Development (CIDESI), Av. Playa Pie de la Cuesta 702 Col. Desarrollo San Pablo, Quer\u00e9taro 76125, M\u00e9xico;"},{"name":"Research Center for Applied Science and Advanced Technology (CICATA), Cerro Blanco 141 Col. Colinas del Cimatario, Quer\u00e9taro 76090, M\u00e9xico"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"33","published-online":{"date-parts":[[2020,2,24]]},"reference":[{"key":"2020022410492414700_CIT0001","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.cad.2017.07.005","article-title":"Urban Building Reconstruction From Raw Lidar Point Data","volume":"93","author":"Yi","year":"2017","journal-title":"Compu.-Aided Des."},{"key":"2020022410492414700_CIT0002","doi-asserted-by":"crossref","DOI":"10.5194\/isprs-annals-IV-2-49-2018","article-title":"Large Scale Textured Mesh Reconstruction From Mobile Mapping Images and LIDAR Scans","author":"Boussaha","year":"2018"},{"key":"2020022410492414700_CIT0003","first-page":"5079","article-title":"Meaningful Maps with Object-Oriented Semantic Mapping","author":"S\u00fcnderhauf","year":"2017"},{"key":"2020022410492414700_CIT0004","first-page":"1","article-title":"Autonomous 2d SLAM and 3d Mapping of an Environment Using a Single 2d Lidar and Ros","author":"Ocando","year":"2017"},{"key":"2020022410492414700_CIT0005","doi-asserted-by":"crossref","DOI":"10.1109\/IROS.2017.8202212","article-title":"Semantic 3D Occupancy Mapping Through Efficient High Order CRFs","author":"Yang","year":"2017"},{"issue":"1","key":"2020022410492414700_CIT0006","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/j.cviu.2011.07.009","article-title":"A Systematic Approach for 2d-image to 3d-range Registration in Urban Environments","volume":"116","author":"Liu","year":"2012","journal-title":"Comput. Vision Image Underst."},{"key":"2020022410492414700_CIT0007","first-page":"137","article-title":"Automatic 3d to 2d Registration for the Photorealistic Rendering of Urban Scenes","author":"Liu","year":"2005"},{"issue":"2\u20133","key":"2020022410492414700_CIT0008","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1007\/s11263-007-0089-1","article-title":"Integrating Automated Range Registration with Multiview Geometry for the Photorealistic Modeling of Large-scale Scenes","volume":"78","author":"Stamos","year":"2008","journal-title":"Int. J. Comput. Vision"},{"key":"2020022410492414700_CIT0009","article-title":"Automatic Targetless Extrinsic Calibration of a 3d LIDAR and Camera by Maximizing Mutual Information","author":"Pandey","year":"2012","journal-title":"Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence"},{"issue":"5","key":"2020022410492414700_CIT0010","doi-asserted-by":"crossref","first-page":"696","DOI":"10.1002\/rob.21542","article-title":"Automatic Extrinsic Calibration of Vision and Lidar by Maximizing Mutual Information","volume":"32","author":"Pandey","year":"2014","journal-title":"J. Field Rob."},{"key":"2020022410492414700_CIT0011","first-page":"012160","article-title":"The Algorithm to Generate Color Point-cloud With the Registration Between Panoramic Image and Laser Point-cloud","author":"Zeng","year":"2014"},{"key":"2020022410492414700_CIT0012","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1016\/j.imavis.2015.06.002","article-title":"Fusion of a Panoramic Camera and 2d Laser Scanner Data for Constrained Bundle Adjustment in Gps-denied Environments","volume":"40","author":"Shi","year":"2015","journal-title":"Image Vision Comput."},{"issue":"7","key":"2020022410492414700_CIT0013","doi-asserted-by":"crossref","first-page":"1406","DOI":"10.3390\/rs3071406","article-title":"Photorealistic Building Reconstruction From Mobile Laser Scanning Data","volume":"3","author":"Zhu","year":"2011","journal-title":"Remote Sens."},{"issue":"6","key":"2020022410492414700_CIT0014","doi-asserted-by":"crossref","first-page":"639","DOI":"10.1016\/j.cad.2011.02.012","article-title":"A New Mesh-growing Algorithm for Fast Surface Reconstruction","volume":"43","author":"Di Angelo","year":"2011","journal-title":"Comput.-Aided Design"},{"key":"2020022410492414700_CIT0015","first-page":"67","article-title":"Reconstruction and Representation of 3d Objects With Radial Basis Functions","author":"Carr","year":"2001"},{"key":"2020022410492414700_CIT0016","first-page":"415","article-title":"A New Voronoi-Based Surface Reconstruction Algorithm","author":"Amenta","year":"1998"},{"issue":"1","key":"2020022410492414700_CIT0017","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1007\/s00371-003-0217-z","article-title":"A Greedy Delaunay-based Surface Reconstruction Algorithm","volume":"20","author":"Cohen-Steiner","year":"2004","journal-title":"Visual Comput."},{"key":"2020022410492414700_CIT0018","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1007\/978-3-540-33259-6_6","volume-title":"Effective Computational Geometry for Curves and Surfaces","author":"Cazals","year":"2006"},{"issue":"4","key":"2020022410492414700_CIT0019","doi-asserted-by":"crossref","first-page":"349","DOI":"10.1109\/2945.817351","article-title":"The Ball-Pivoting Algorithm for Surface Reconstruction","volume":"5","author":"Bernardini","year":"1999","journal-title":"IEEE Trans. Vis. Comput. Graph."},{"article-title":"Poisson Surface Reconstruction","year":"2006","author":"Kazhdan","key":"2020022410492414700_CIT0020"},{"issue":"3","key":"2020022410492414700_CIT0021","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1145\/2487228.2487237","article-title":"Screened Poisson Surface Reconstruction","volume":"32","author":"Kazhdan","year":"2013","journal-title":"ACM Trans. Graph. (TOG)"},{"issue":"2","key":"2020022410492414700_CIT0022","doi-asserted-by":"crossref","first-page":"024002","DOI":"10.1117\/1.JRS.10.024002","article-title":"Accurate Evaluation of Sensitivity for Calibration Between a Lidar and a Panoramic Camera Used for Remote Sensing","volume":"10","author":"Garc\u00eda-Moreno","year":"2016","journal-title":"J. Appl. Remote Sens."},{"volume-title":"Pattern Recognition","year":"2013","author":"Garc\u00eda-Moreno","key":"2020022410492414700_CIT0023"},{"issue":"3","key":"2020022410492414700_CIT0024","doi-asserted-by":"crossref","first-page":"146","DOI":"10.1007\/BF01784024","article-title":"Probabilistic Clock Synchronization","volume":"3","author":"Cristian","year":"1989","journal-title":"Distrib. Comput."},{"issue":"4","key":"2020022410492414700_CIT0025","doi-asserted-by":"crossref","first-page":"1167","DOI":"10.1016\/j.csda.2009.09.020","article-title":"Robust Smoothing of Gridded Data in One and Higher Dimensions With Missing Values","volume":"54","author":"Garcia","year":"2010","journal-title":"Comput. Stat. Data Anal."},{"issue":"13","key":"2020022410492414700_CIT0026","doi-asserted-by":"crossref","first-page":"1543","DOI":"10.1177\/0278364911400640","article-title":"Ford Campus Vision and Lidar Data Set","volume":"30","author":"Pandey","year":"2011","journal-title":"Int. J. Rob. Res."},{"key":"2020022410492414700_CIT0027","first-page":"263","volume-title":"Active Vision","author":"Harris","year":"1993"},{"key":"2020022410492414700_CIT0028","first-page":"510","article-title":"Multi-Image Matching Using Multi-Scale Oriented Patches","author":"Brown","year":"2005"},{"issue":"2","key":"2020022410492414700_CIT0029","doi-asserted-by":"crossref","first-page":"457","DOI":"10.1137\/S0097539798347177","article-title":"Efficient Search for Approximate Nearest Neighbor in High Dimensional Spaces","volume":"30","author":"Kushilevitz","year":"2000","journal-title":"SIAM J. Comput."},{"issue":"6","key":"2020022410492414700_CIT0030","doi-asserted-by":"crossref","first-page":"782","DOI":"10.1016\/j.robot.2014.02.004","article-title":"Error Propagation and Uncertainty Analysis Between 3d Laser Scanner and Camera","volume":"62","author":"Garc\u00eda-Moreno","year":"2014","journal-title":"Rob. Auton. Syst."},{"volume-title":"Multiple View Geometry in Computer Vision","year":"2000","author":"Hartley","key":"2020022410492414700_CIT0031"},{"key":"2020022410492414700_CIT0032","first-page":"145","article-title":"Efficient Variants of the ICP Algorithm","author":"Rusinkiewicz","year":"2001"},{"issue":"4","key":"2020022410492414700_CIT0033","doi-asserted-by":"crossref","first-page":"407","DOI":"10.14358\/PERS.76.4.407","article-title":"Automatic Segmentation of Lidar Data Into Coplanar Point Clusters Using An Octree-based Split-and-merge Algorithm","volume":"76","author":"Wang","year":"2010","journal-title":"Photogramm. Eng. Remote Sens."}],"container-title":["Journal of Computing and Information Science in Engineering"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/asmedigitalcollection.asme.org\/computingengineering\/article-pdf\/doi\/10.1115\/1.4045172\/6487360\/jcise_20_4_044501.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"http:\/\/asmedigitalcollection.asme.org\/computingengineering\/article-pdf\/doi\/10.1115\/1.4045172\/6487360\/jcise_20_4_044501.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,2,24]],"date-time":"2020-02-24T15:49:46Z","timestamp":1582559386000},"score":1,"resource":{"primary":{"URL":"https:\/\/asmedigitalcollection.asme.org\/computingengineering\/article\/doi\/10.1115\/1.4045172\/1065627\/Dynamic-MultiSensor-Platform-for-Efficient"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,2,24]]},"references-count":33,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2020,8,1]]}},"URL":"https:\/\/doi.org\/10.1115\/1.4045172","relation":{},"ISSN":["1530-9827","1944-7078"],"issn-type":[{"type":"print","value":"1530-9827"},{"type":"electronic","value":"1944-7078"}],"subject":[],"published":{"date-parts":[[2020,2,24]]},"article-number":"044501"}}