BigSUR: large-scale structured urban reconstruction

Handle URI:
http://hdl.handle.net/10754/626748
Title:
BigSUR: large-scale structured urban reconstruction
Authors:
Kelly, Tom; Femiani, John; Wonka, Peter ( 0000-0003-0627-9746 ) ; Mitra, Niloy J.
Abstract:
The creation of high-quality semantically parsed 3D models for dense metropolitan areas is a fundamental urban modeling problem. Although recent advances in acquisition techniques and processing algorithms have resulted in large-scale imagery or 3D polygonal reconstructions, such data-sources are typically noisy, and incomplete, with no semantic structure. In this paper, we present an automatic data fusion technique that produces high-quality structured models of city blocks. From coarse polygonal meshes, street-level imagery, and GIS footprints, we formulate a binary integer program that globally balances sources of error to produce semantically parsed mass models with associated facade elements. We demonstrate our system on four city regions of varying complexity; our examples typically contain densely built urban blocks spanning hundreds of buildings. In our largest example, we produce a structured model of 37 city blocks spanning a total of 1,011 buildings at a scale and quality previously impossible to achieve automatically.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division; Computer Science Program; Visual Computing Center (VCC)
Citation:
Kelly T, Femiani J, Wonka P, Mitra NJ (2017) BigSUR. ACM Transactions on Graphics 36: 1–16. Available: http://dx.doi.org/10.1145/3130800.3130823.
Publisher:
Association for Computing Machinery (ACM)
Journal:
ACM Transactions on Graphics
KAUST Grant Number:
OSR-2015-CCF-2533; OCRF-2014-CGR3-62140401
Conference/Event name:
ACM SIGGRAPH Asia Conference, SA 2017
Issue Date:
22-Nov-2017
Embedded Video:
DOI:
10.1145/3130800.3130823
Type:
Conference Paper
ISSN:
0730-0301
Sponsors:
We would like to thank the many people who contributed to this paper; the reviewers, image labellers, and others who read manuscripts, each made valuable contributions. In particular, we thank Florent Lafarge, Pierre Alliez, Pascal Muller, and Lama Affara for providing us with comparisons, software, and sourcecode, as well as Virginia Unkefer, Robin Roussel, Carlo Innamorati, and Aron Monszpart for their feedback. This work was supported by the ERC Starting Grant (SmartGeometry StG-2013-335373), KAUST-UCL grant (OSR-2015-CCF-2533), the KAUST Office of Sponsored Research (award No. OCRF-2014-CGR3-62140401), the Salt River Project Agricultural Improvement and Power District Cooperative Agreement No. 12061288, and the Visual Computing Center (VCC) at KAUST.
Additional Links:
https://dl.acm.org/citation.cfm?doid=3130800.3130823; https://youtu.be/_lHRTBkC-yo
Appears in Collections:
Conference Papers; Computer Science Program; Visual Computing Center (VCC); Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorKelly, Tomen
dc.contributor.authorFemiani, Johnen
dc.contributor.authorWonka, Peteren
dc.contributor.authorMitra, Niloy J.en
dc.date.accessioned2018-01-15T06:10:39Z-
dc.date.available2018-01-15T06:10:39Z-
dc.date.issued2017-11-22en
dc.identifier.citationKelly T, Femiani J, Wonka P, Mitra NJ (2017) BigSUR. ACM Transactions on Graphics 36: 1–16. Available: http://dx.doi.org/10.1145/3130800.3130823.en
dc.identifier.issn0730-0301en
dc.identifier.doi10.1145/3130800.3130823en
dc.identifier.urihttp://hdl.handle.net/10754/626748-
dc.description.abstractThe creation of high-quality semantically parsed 3D models for dense metropolitan areas is a fundamental urban modeling problem. Although recent advances in acquisition techniques and processing algorithms have resulted in large-scale imagery or 3D polygonal reconstructions, such data-sources are typically noisy, and incomplete, with no semantic structure. In this paper, we present an automatic data fusion technique that produces high-quality structured models of city blocks. From coarse polygonal meshes, street-level imagery, and GIS footprints, we formulate a binary integer program that globally balances sources of error to produce semantically parsed mass models with associated facade elements. We demonstrate our system on four city regions of varying complexity; our examples typically contain densely built urban blocks spanning hundreds of buildings. In our largest example, we produce a structured model of 37 city blocks spanning a total of 1,011 buildings at a scale and quality previously impossible to achieve automatically.en
dc.description.sponsorshipWe would like to thank the many people who contributed to this paper; the reviewers, image labellers, and others who read manuscripts, each made valuable contributions. In particular, we thank Florent Lafarge, Pierre Alliez, Pascal Muller, and Lama Affara for providing us with comparisons, software, and sourcecode, as well as Virginia Unkefer, Robin Roussel, Carlo Innamorati, and Aron Monszpart for their feedback. This work was supported by the ERC Starting Grant (SmartGeometry StG-2013-335373), KAUST-UCL grant (OSR-2015-CCF-2533), the KAUST Office of Sponsored Research (award No. OCRF-2014-CGR3-62140401), the Salt River Project Agricultural Improvement and Power District Cooperative Agreement No. 12061288, and the Visual Computing Center (VCC) at KAUST.en
dc.publisherAssociation for Computing Machinery (ACM)en
dc.relation.urlhttps://dl.acm.org/citation.cfm?doid=3130800.3130823en
dc.relation.urlhttps://youtu.be/_lHRTBkC-yoen
dc.rightsArchived with thanks to ACM Transactions on Graphicsen
dc.subjecturban modelingen
dc.subjectstructureen
dc.subjectreconstructionen
dc.subjectfacade parsing and element classificationen
dc.subjectprocedural modelingen
dc.titleBigSUR: large-scale structured urban reconstructionen
dc.typeConference Paperen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.contributor.departmentComputer Science Programen
dc.contributor.departmentVisual Computing Center (VCC)en
dc.identifier.journalACM Transactions on Graphicsen
dc.conference.date2017-11-27 to 2017-11-30en
dc.conference.nameACM SIGGRAPH Asia Conference, SA 2017en
dc.conference.locationBangkok, THAen
dc.eprint.versionPublisher's Version/PDFen
dc.contributor.institutionUniversity College Londonen
dc.contributor.institutionMiami Universityen
dc.relation.embedded<iframe width="560" height="315" src="https://www.youtube.com/embed/_lHRTBkC-yo?rel=0" frameborder="0" allow="autoplay; encrypted-media" allowfullscreen></iframe>-
kaust.authorWonka, Peteren
kaust.grant.numberOSR-2015-CCF-2533en
kaust.grant.numberOCRF-2014-CGR3-62140401en
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