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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

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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...

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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
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.
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