No Cover Image

Journal article 337 views 129 downloads

Survey on 3D Reconstruction Techniques: Large-Scale Urban City Reconstruction and Requirements

Andreas Christodoulides, Gary Tam Orcid Logo, James Clarke, Richard Smith Orcid Logo, Jon Horgan, Nicholas Micallef Orcid Logo, Jeremy Morley, Nelly Villamizar Orcid Logo, Sean Walton Orcid Logo

IEEE Transactions on Visualization and Computer Graphics

Swansea University Authors: Andreas Christodoulides, Gary Tam Orcid Logo, Richard Smith Orcid Logo, Nicholas Micallef Orcid Logo, Nelly Villamizar Orcid Logo, Sean Walton Orcid Logo

  • 68829.AAM with CC-BY.pdf

    PDF | Accepted Manuscript

    Author accepted manuscript document released under the terms of a Creative Commons CC-BY licence using the Swansea University Research Publications Policy.

    Download (3.18MB)

Abstract

3D representations of large-scale and urban scenes are crucial across various industries, including autonomous driving, urban planning, natural resource supervision and many more. Large-scale industrial reconstructions are inherently complex and multifaceted. Many existing surveys primarily focus on...

Full description

Published in: IEEE Transactions on Visualization and Computer Graphics
ISSN: 1077-2626 1941-0506
Published: IEEE 2025
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa68829
first_indexed 2025-02-07T13:15:00Z
last_indexed 2025-05-03T04:42:01Z
id cronfa68829
recordtype SURis
fullrecord <?xml version="1.0"?><rfc1807><datestamp>2025-05-02T14:12:01.2585566</datestamp><bib-version>v2</bib-version><id>68829</id><entry>2025-02-07</entry><title>Survey on 3D Reconstruction Techniques: Large-Scale Urban City Reconstruction and Requirements</title><swanseaauthors><author><sid>26e0abf1d9763a390d51a769433893cc</sid><firstname>Andreas</firstname><surname>Christodoulides</surname><name>Andreas Christodoulides</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>e75a68e11a20e5f1da94ee6e28ff5e76</sid><ORCID>0000-0001-7387-5180</ORCID><firstname>Gary</firstname><surname>Tam</surname><name>Gary Tam</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>c91a932b3bc4c9ab9297b67800c95e08</sid><ORCID>0000-0003-0318-8494</ORCID><firstname>Richard</firstname><surname>Smith</surname><name>Richard Smith</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>1cc4c84582d665b7ee08fb16f5454671</sid><ORCID>0000-0002-2683-8042</ORCID><firstname>Nicholas</firstname><surname>Micallef</surname><name>Nicholas Micallef</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>41572bcee47da6ba274ecd1828fbfef4</sid><ORCID>0000-0002-8741-7225</ORCID><firstname>Nelly</firstname><surname>Villamizar</surname><name>Nelly Villamizar</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>0ec10d5e3ed3720a2d578417a894cf49</sid><ORCID>0000-0002-6451-265X</ORCID><firstname>Sean</firstname><surname>Walton</surname><name>Sean Walton</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2025-02-07</date><deptcode>MACS</deptcode><abstract>3D representations of large-scale and urban scenes are crucial across various industries, including autonomous driving, urban planning, natural resource supervision and many more. Large-scale industrial reconstructions are inherently complex and multifaceted. Many existing surveys primarily focus on academic progressions and often neglect the intricate and diverse needs of industry. This survey aims to bridge this gap by providing a comprehensive analysis of 3D reconstruction methods, with a focus on industrial requirements such as scalability and integration of human interaction. Our approach involves utilizing Affinity Diagramming to systematically analyze qualitative data gathered from industrial partners. This methodology enables us to gain deep insights into how recent literature addresses these specific industrial needs. The survey encompasses various aspects, including input and reconstruction modalities, architectural models, datasets, evaluation metrics, and the incorporation of prior knowledge. We further discuss practical implications derived from our analysis, highlighting key considerations for future advancements in 3D reconstruction methods tailored for large-scale applications.</abstract><type>Journal Article</type><journal>IEEE Transactions on Visualization and Computer Graphics</journal><volume>0</volume><journalNumber/><paginationStart/><paginationEnd/><publisher>IEEE</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint>1077-2626</issnPrint><issnElectronic>1941-0506</issnElectronic><keywords>Three-dimensional displays, Image reconstruction, Surveys, Solid modeling, Deep learning, Surface reconstruction, Simultaneous localization and mapping, Scalability, Point cloud compression, Computational modeling</keywords><publishedDay>19</publishedDay><publishedMonth>2</publishedMonth><publishedYear>2025</publishedYear><publishedDate>2025-02-19</publishedDate><doi>10.1109/TVCG.2025.3540669</doi><url/><notes/><college>COLLEGE NANME</college><department>Mathematics and Computer Science School</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>MACS</DepartmentCode><institution>Swansea University</institution><apcterm>Not Required</apcterm><funders>EPSRC, EP/S021892/1</funders><projectreference/><lastEdited>2025-05-02T14:12:01.2585566</lastEdited><Created>2025-02-07T13:09:58.9841788</Created><path><level id="1">Faculty of Science and Engineering</level><level id="2">School of Mathematics and Computer Science - Computer Science</level></path><authors><author><firstname>Andreas</firstname><surname>Christodoulides</surname><order>1</order></author><author><firstname>Gary</firstname><surname>Tam</surname><orcid>0000-0001-7387-5180</orcid><order>2</order></author><author><firstname>James</firstname><surname>Clarke</surname><order>3</order></author><author><firstname>Richard</firstname><surname>Smith</surname><orcid>0000-0003-0318-8494</orcid><order>4</order></author><author><firstname>Jon</firstname><surname>Horgan</surname><order>5</order></author><author><firstname>Nicholas</firstname><surname>Micallef</surname><orcid>0000-0002-2683-8042</orcid><order>6</order></author><author><firstname>Jeremy</firstname><surname>Morley</surname><order>7</order></author><author><firstname>Nelly</firstname><surname>Villamizar</surname><orcid>0000-0002-8741-7225</orcid><order>8</order></author><author><firstname>Sean</firstname><surname>Walton</surname><orcid>0000-0002-6451-265X</orcid><order>9</order></author></authors><documents><document><filename>68829__33652__6a444609384e43feb4b347e818119679.pdf</filename><originalFilename>68829.AAM with CC-BY.pdf</originalFilename><uploaded>2025-02-19T15:54:46.8692273</uploaded><type>Output</type><contentLength>3333216</contentLength><contentType>application/pdf</contentType><version>Accepted Manuscript</version><cronfaStatus>true</cronfaStatus><embargoDate>2025-03-15T00:00:00.0000000</embargoDate><documentNotes>Author accepted manuscript document released under the terms of a Creative Commons CC-BY licence using the Swansea University Research Publications Policy.</documentNotes><copyrightCorrect>true</copyrightCorrect><language>eng</language><licence>https://creativecommons.org/licenses/by/4.0/</licence></document></documents><OutputDurs/></rfc1807>
spelling 2025-05-02T14:12:01.2585566 v2 68829 2025-02-07 Survey on 3D Reconstruction Techniques: Large-Scale Urban City Reconstruction and Requirements 26e0abf1d9763a390d51a769433893cc Andreas Christodoulides Andreas Christodoulides true false e75a68e11a20e5f1da94ee6e28ff5e76 0000-0001-7387-5180 Gary Tam Gary Tam true false c91a932b3bc4c9ab9297b67800c95e08 0000-0003-0318-8494 Richard Smith Richard Smith true false 1cc4c84582d665b7ee08fb16f5454671 0000-0002-2683-8042 Nicholas Micallef Nicholas Micallef true false 41572bcee47da6ba274ecd1828fbfef4 0000-0002-8741-7225 Nelly Villamizar Nelly Villamizar true false 0ec10d5e3ed3720a2d578417a894cf49 0000-0002-6451-265X Sean Walton Sean Walton true false 2025-02-07 MACS 3D representations of large-scale and urban scenes are crucial across various industries, including autonomous driving, urban planning, natural resource supervision and many more. Large-scale industrial reconstructions are inherently complex and multifaceted. Many existing surveys primarily focus on academic progressions and often neglect the intricate and diverse needs of industry. This survey aims to bridge this gap by providing a comprehensive analysis of 3D reconstruction methods, with a focus on industrial requirements such as scalability and integration of human interaction. Our approach involves utilizing Affinity Diagramming to systematically analyze qualitative data gathered from industrial partners. This methodology enables us to gain deep insights into how recent literature addresses these specific industrial needs. The survey encompasses various aspects, including input and reconstruction modalities, architectural models, datasets, evaluation metrics, and the incorporation of prior knowledge. We further discuss practical implications derived from our analysis, highlighting key considerations for future advancements in 3D reconstruction methods tailored for large-scale applications. Journal Article IEEE Transactions on Visualization and Computer Graphics 0 IEEE 1077-2626 1941-0506 Three-dimensional displays, Image reconstruction, Surveys, Solid modeling, Deep learning, Surface reconstruction, Simultaneous localization and mapping, Scalability, Point cloud compression, Computational modeling 19 2 2025 2025-02-19 10.1109/TVCG.2025.3540669 COLLEGE NANME Mathematics and Computer Science School COLLEGE CODE MACS Swansea University Not Required EPSRC, EP/S021892/1 2025-05-02T14:12:01.2585566 2025-02-07T13:09:58.9841788 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Andreas Christodoulides 1 Gary Tam 0000-0001-7387-5180 2 James Clarke 3 Richard Smith 0000-0003-0318-8494 4 Jon Horgan 5 Nicholas Micallef 0000-0002-2683-8042 6 Jeremy Morley 7 Nelly Villamizar 0000-0002-8741-7225 8 Sean Walton 0000-0002-6451-265X 9 68829__33652__6a444609384e43feb4b347e818119679.pdf 68829.AAM with CC-BY.pdf 2025-02-19T15:54:46.8692273 Output 3333216 application/pdf Accepted Manuscript true 2025-03-15T00:00:00.0000000 Author accepted manuscript document released under the terms of a Creative Commons CC-BY licence using the Swansea University Research Publications Policy. true eng https://creativecommons.org/licenses/by/4.0/
title Survey on 3D Reconstruction Techniques: Large-Scale Urban City Reconstruction and Requirements
spellingShingle Survey on 3D Reconstruction Techniques: Large-Scale Urban City Reconstruction and Requirements
Andreas Christodoulides
Gary Tam
Richard Smith
Nicholas Micallef
Nelly Villamizar
Sean Walton
title_short Survey on 3D Reconstruction Techniques: Large-Scale Urban City Reconstruction and Requirements
title_full Survey on 3D Reconstruction Techniques: Large-Scale Urban City Reconstruction and Requirements
title_fullStr Survey on 3D Reconstruction Techniques: Large-Scale Urban City Reconstruction and Requirements
title_full_unstemmed Survey on 3D Reconstruction Techniques: Large-Scale Urban City Reconstruction and Requirements
title_sort Survey on 3D Reconstruction Techniques: Large-Scale Urban City Reconstruction and Requirements
author_id_str_mv 26e0abf1d9763a390d51a769433893cc
e75a68e11a20e5f1da94ee6e28ff5e76
c91a932b3bc4c9ab9297b67800c95e08
1cc4c84582d665b7ee08fb16f5454671
41572bcee47da6ba274ecd1828fbfef4
0ec10d5e3ed3720a2d578417a894cf49
author_id_fullname_str_mv 26e0abf1d9763a390d51a769433893cc_***_Andreas Christodoulides
e75a68e11a20e5f1da94ee6e28ff5e76_***_Gary Tam
c91a932b3bc4c9ab9297b67800c95e08_***_Richard Smith
1cc4c84582d665b7ee08fb16f5454671_***_Nicholas Micallef
41572bcee47da6ba274ecd1828fbfef4_***_Nelly Villamizar
0ec10d5e3ed3720a2d578417a894cf49_***_Sean Walton
author Andreas Christodoulides
Gary Tam
Richard Smith
Nicholas Micallef
Nelly Villamizar
Sean Walton
author2 Andreas Christodoulides
Gary Tam
James Clarke
Richard Smith
Jon Horgan
Nicholas Micallef
Jeremy Morley
Nelly Villamizar
Sean Walton
format Journal article
container_title IEEE Transactions on Visualization and Computer Graphics
container_volume 0
publishDate 2025
institution Swansea University
issn 1077-2626
1941-0506
doi_str_mv 10.1109/TVCG.2025.3540669
publisher IEEE
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Mathematics and Computer Science - Computer Science{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Computer Science
document_store_str 1
active_str 0
description 3D representations of large-scale and urban scenes are crucial across various industries, including autonomous driving, urban planning, natural resource supervision and many more. Large-scale industrial reconstructions are inherently complex and multifaceted. Many existing surveys primarily focus on academic progressions and often neglect the intricate and diverse needs of industry. This survey aims to bridge this gap by providing a comprehensive analysis of 3D reconstruction methods, with a focus on industrial requirements such as scalability and integration of human interaction. Our approach involves utilizing Affinity Diagramming to systematically analyze qualitative data gathered from industrial partners. This methodology enables us to gain deep insights into how recent literature addresses these specific industrial needs. The survey encompasses various aspects, including input and reconstruction modalities, architectural models, datasets, evaluation metrics, and the incorporation of prior knowledge. We further discuss practical implications derived from our analysis, highlighting key considerations for future advancements in 3D reconstruction methods tailored for large-scale applications.
published_date 2025-02-19T07:40:07Z
_version_ 1836697473031077888
score 11.06703