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Point Cloud Completion: A Survey

Keneni Tesema, Lyndon Hill Orcid Logo, Mark Jones Orcid Logo, Muneeb Ahmad Orcid Logo, Gary Tam Orcid Logo

IEEE Transactions on Visualization and Computer Graphics, Pages: 1 - 20

Swansea University Authors: Keneni Tesema, Mark Jones Orcid Logo, Muneeb Ahmad Orcid Logo, Gary Tam Orcid Logo

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Abstract

Point cloud completion is the task of producing a complete 3D shape given an input of a partial point cloud. It has become a vital process in 3D computer graphics, vision and applications such as autonomous driving, robotics, and augmented reality. These applications often rely on the presence of a...

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Published in: IEEE Transactions on Visualization and Computer Graphics
ISSN: 1077-2626 1941-0506
Published: Institute of Electrical and Electronics Engineers (IEEE) 2024
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URI: https://cronfa.swan.ac.uk/Record/cronfa65337
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It has become a vital process in 3D computer graphics, vision and applications such as autonomous driving, robotics, and augmented reality. These applications often rely on the presence of a complete 3D representation of the environment. Over the past few years, many completion algorithms have been proposed and a substantial amount of research has been carried out. However, there are not many in-depth surveys that summarise the research progress in such a way that allows users to make an informed choice of what algorithms to employ given the type of data they have, the end result they want, the challenges they may face and the possible strategies they could use. In this study, we present a comprehensive survey and classification of papers on point cloud completion until August 2023 based on the strategies, techniques, inputs, outputs, and network architectures. We will also cover datasets, evaluation methods, and application areas in point cloud completion. 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spelling v2 65337 2023-12-18 Point Cloud Completion: A Survey 565d5e98f266077e36258ac9c10b2a80 Keneni Tesema Keneni Tesema true false 2e1030b6e14fc9debd5d5ae7cc335562 0000-0001-8991-1190 Mark Jones Mark Jones true false 9c42fd947397b1ad2bfa9107457974d5 0000-0001-8111-9967 Muneeb Ahmad Muneeb Ahmad true false e75a68e11a20e5f1da94ee6e28ff5e76 0000-0001-7387-5180 Gary Tam Gary Tam true false 2023-12-18 FGSEN Point cloud completion is the task of producing a complete 3D shape given an input of a partial point cloud. It has become a vital process in 3D computer graphics, vision and applications such as autonomous driving, robotics, and augmented reality. These applications often rely on the presence of a complete 3D representation of the environment. Over the past few years, many completion algorithms have been proposed and a substantial amount of research has been carried out. However, there are not many in-depth surveys that summarise the research progress in such a way that allows users to make an informed choice of what algorithms to employ given the type of data they have, the end result they want, the challenges they may face and the possible strategies they could use. In this study, we present a comprehensive survey and classification of papers on point cloud completion until August 2023 based on the strategies, techniques, inputs, outputs, and network architectures. We will also cover datasets, evaluation methods, and application areas in point cloud completion. Finally, we discuss challenges faced by the research community and future research directions. Journal Article IEEE Transactions on Visualization and Computer Graphics 1 20 Institute of Electrical and Electronics Engineers (IEEE) 1077-2626 1941-0506 Point cloud compression, Shape, Surveys, Three-dimensional displays, Semantics,Task analysis, Surface reconstruction 1 1 2024 2024-01-01 10.1109/tvcg.2023.3344935 http://dx.doi.org/10.1109/tvcg.2023.3344935 COLLEGE NANME Science and Engineering - Faculty COLLEGE CODE FGSEN Swansea University External research funder(s) paid the OA fee (includes OA grants disbursed by the Library) EPSRC, Royal Society, EP/S021892/1, IEC/NSFC/211159 2024-03-25T11:58:20.0425208 2023-12-18T08:17:35.9377764 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Keneni Tesema 1 Lyndon Hill 0009-0001-9276-2891 2 Mark Jones 0000-0001-8991-1190 3 Muneeb Ahmad 0000-0001-8111-9967 4 Gary Tam 0000-0001-7387-5180 5 65337__29823__3c0bbe3d12124926847f42eae69cbfd9.pdf 65337.VOR.pdf 2024-03-25T11:56:21.7400831 Output 9712869 application/pdf Version of Record true This work is licensed under a Creative Commons Attribution 4.0 License (CC-BY) true eng https://creativecommons.org/licenses/by/4.0/
title Point Cloud Completion: A Survey
spellingShingle Point Cloud Completion: A Survey
Keneni Tesema
Mark Jones
Muneeb Ahmad
Gary Tam
title_short Point Cloud Completion: A Survey
title_full Point Cloud Completion: A Survey
title_fullStr Point Cloud Completion: A Survey
title_full_unstemmed Point Cloud Completion: A Survey
title_sort Point Cloud Completion: A Survey
author_id_str_mv 565d5e98f266077e36258ac9c10b2a80
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author_id_fullname_str_mv 565d5e98f266077e36258ac9c10b2a80_***_Keneni Tesema
2e1030b6e14fc9debd5d5ae7cc335562_***_Mark Jones
9c42fd947397b1ad2bfa9107457974d5_***_Muneeb Ahmad
e75a68e11a20e5f1da94ee6e28ff5e76_***_Gary Tam
author Keneni Tesema
Mark Jones
Muneeb Ahmad
Gary Tam
author2 Keneni Tesema
Lyndon Hill
Mark Jones
Muneeb Ahmad
Gary Tam
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publishDate 2024
institution Swansea University
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doi_str_mv 10.1109/tvcg.2023.3344935
publisher Institute of Electrical and Electronics Engineers (IEEE)
college_str Faculty of Science and Engineering
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url http://dx.doi.org/10.1109/tvcg.2023.3344935
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description Point cloud completion is the task of producing a complete 3D shape given an input of a partial point cloud. It has become a vital process in 3D computer graphics, vision and applications such as autonomous driving, robotics, and augmented reality. These applications often rely on the presence of a complete 3D representation of the environment. Over the past few years, many completion algorithms have been proposed and a substantial amount of research has been carried out. However, there are not many in-depth surveys that summarise the research progress in such a way that allows users to make an informed choice of what algorithms to employ given the type of data they have, the end result they want, the challenges they may face and the possible strategies they could use. In this study, we present a comprehensive survey and classification of papers on point cloud completion until August 2023 based on the strategies, techniques, inputs, outputs, and network architectures. We will also cover datasets, evaluation methods, and application areas in point cloud completion. Finally, we discuss challenges faced by the research community and future research directions.
published_date 2024-01-01T11:58:16Z
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