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Survey on 3D Reconstruction Techniques: Large-Scale Urban City Reconstruction and Requirements
IEEE Transactions on Visualization and Computer Graphics
Swansea University Authors:
Andreas Christodoulides, Gary Tam , Richard Smith
, Nicholas Micallef
, Nelly Villamizar
, Sean Walton
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Author accepted manuscript document released under the terms of a Creative Commons CC-BY licence using the Swansea University Research Publications Policy.
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DOI (Published version): 10.1109/TVCG.2025.3540669
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...
Published in: | IEEE Transactions on Visualization and Computer Graphics |
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ISSN: | 1077-2626 1941-0506 |
Published: |
IEEE
2025
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Online Access: |
Check full text
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URI: | https://cronfa.swan.ac.uk/Record/cronfa68829 |
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. |
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Keywords: |
Three-dimensional displays, Image reconstruction, Surveys, Solid modeling, Deep learning, Surface reconstruction, Simultaneous localization and mapping, Scalability, Point cloud compression, Computational modeling |
College: |
Faculty of Science and Engineering |
Funders: |
EPSRC, EP/S021892/1 |