Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/110869
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dc.contributorSchool of Fashion and Textiles-
dc.creatorLiu, QLen_US
dc.creatorYick, KLen_US
dc.creatorSun, Yen_US
dc.creatorYip, Jen_US
dc.date.accessioned2025-02-11T05:01:00Z-
dc.date.available2025-02-11T05:01:00Z-
dc.identifier.urihttp://hdl.handle.net/10397/110869-
dc.language.isoenen_US
dc.publisherPublic Library of Scienceen_US
dc.rights© 2024 Liu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.en_US
dc.rightsThe following publication Liu Q-l, Yick K-l, Sun Y, Yip J (2024) Ultra-dense Motion Capture: An exploratory full-automatic approach for dense tracking of breast motion in 4D. PLoS ONE 19(2): e0299040 is available at https://doi.org/10.1371/journal.pone.0299040.en_US
dc.titleUltra-dense motion capture : an exploratory full-automatic approach for dense tracking of breast motion in 4Den_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume19en_US
dc.identifier.doi10.1371/journal.pone.0299040en_US
dcterms.abstractUnderstanding the dynamic deformation pattern and biomechanical properties of breasts is crucial in various fields, including designing ergonomic bras and customized prostheses, as well as in clinical practice. Previous studies have recorded and analyzed the dynamic behaviors of the breast surface using 4D scanning, which provides a sequence of 3D meshes during movement with high spatial and temporal resolutions. However, these studies are limited by the lack of robust and automated data processing methods which result in limited data coverage or error-prone analysis results. To address this issue, we identify revealing inter-frame dense correspondence as the core challenge towards conducting reliable and consistent analysis of the 4D scanning data. We proposed a fully-automatic approach named Ulta-dense Motion Capture (UdMC) using Thin-plate Spline (TPS) to augment the sparse landmarks recorded via motion capture (MoCap) as initial dense correspondence and then rectified it with a sophisticated post-alignment scheme. Two downstream tasks are demonstrated to validate its applicability: virtual landmark tracking and deformation intensity analysis. For evaluation, a dynamic 4D human breast anthropometric dataset DynaBreastLite was constructed. The results show that our approach can robustly capture the dynamic deformation characteristics of the breast surfaces, significantly outperforms baselines adapted from previous works in terms of accuracy, consistency, and efficiency. For 10 fps dataset, average error of 0.25 cm on control-landmarks and 0.33 cm on non-control (arbitrary) landmarks were achieved, with 17-70 times faster computation time. Evaluation was also carried out on 60 fps and 120 fps datasets, with consistent and large performance gaining being observed. The proposed method may contribute to advancing research in breast anthropometry, biomechanics, and ergonomics by enabling more accurate tracking of the breast surface deformation patterns and dynamic characteristics.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationPLoS one, 26 Feb. 2024, v. 19, e0299040en_US
dcterms.isPartOfPLoS oneen_US
dcterms.issued2024-02-26-
dc.identifier.scopus2-s2.0-85186092976-
dc.identifier.pmid38408041-
dc.identifier.eissn1932-6203en_US
dc.identifier.artne0299040en_US
dc.description.validate202502 bcwh-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Others-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextInnovation and Technology Fund; Laboratory for Artificial Intelligence in Design, Innovation and Technology Fund, Hong Kongen_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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