Robust 3D Human Motion Reconstruction from Multi-View Mobile Videos for Quantitative Ski Technique Analysis

Robust 3D Human Motion Reconstruction from Multi-View Mobile Videos for Quantitative Ski Technique Analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Robust 3D Human Motion Reconstruction from Multi-View Mobile Videos for Quantitative Ski Technique Analysis Kaixu Chen, Chun Xie, Eiichi Naito, Toshitaka Kimura, Itaru Kitahara This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9263053/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Quantitative evaluation of skiing technique in real-world settings is inherently challenging due to complex whole-body coordination, rapid posture transitions, and frequent viewpoint changes during motion. Conventional assessment still relies heavily on expert observation, which is subjective and difficult to standardize. In addition, many existing motion-analysis pipelines assume fixed and calibrated camera setups, which limits practical deployment in realistic skiing environments. In this study, we present a practical multi-view framework for reconstructing stable 3D human poses from synchronized mobile videos without requiring fixed camera setups or prior calibration. The framework integrates skier tracking, single-view 3D pose estimation, canonical alignment, confidence-guided multi-view fusion, and temporal smoothing. Experiments on real skiing videos show that multi-view fusion improves the spatial consistency and temporal stability of reconstructed 3D poses and supports interpretable analysis of posture stability, joint kinematics, and inter-limb coordination, including observable differences between skiers with different experience levels. On simulated skiing data with ground truth, the proposed method achieves a fused 3D MPJPE of 0.5130, improving over single-view baselines of 0.7950 and 0.8498. The proposed framework provides a scalable and camera-agnostic solution for quantitative sports motion analysis and can be extended to other complex whole-body activities beyond skiing. Physical sciences/Engineering Physical sciences/Mathematics and computing Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 16 May, 2026 Reviewers agreed at journal 13 May, 2026 Reviews received at journal 15 Apr, 2026 Reviewers agreed at journal 09 Apr, 2026 Reviewers invited by journal 07 Apr, 2026 Editor assigned by journal 07 Apr, 2026 Editor invited by journal 06 Apr, 2026 Submission checks completed at journal 02 Apr, 2026 First submitted to journal 02 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9263053","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":622325481,"identity":"ee3ea044-d94b-49c9-bce3-433a989f6a2d","order_by":0,"name":"Kaixu Chen","email":"","orcid":"","institution":"University of Tsukuba","correspondingAuthor":false,"prefix":"","firstName":"Kaixu","middleName":"","lastName":"Chen","suffix":""},{"id":622325486,"identity":"868d52af-897d-4abf-a277-b3e5eb0d081b","order_by":1,"name":"Chun Xie","email":"","orcid":"","institution":"University of Tsukuba","correspondingAuthor":false,"prefix":"","firstName":"Chun","middleName":"","lastName":"Xie","suffix":""},{"id":622325487,"identity":"fd7caa2d-b447-4f52-9abc-a0c1fd37f834","order_by":2,"name":"Eiichi Naito","email":"","orcid":"","institution":"National Institute of Information and Communications Technology","correspondingAuthor":false,"prefix":"","firstName":"Eiichi","middleName":"","lastName":"Naito","suffix":""},{"id":622325495,"identity":"edfca0af-2389-4b6b-a782-7fa7794e4e6c","order_by":3,"name":"Toshitaka Kimura","email":"","orcid":"","institution":"NTT (Japan)","correspondingAuthor":false,"prefix":"","firstName":"Toshitaka","middleName":"","lastName":"Kimura","suffix":""},{"id":622325497,"identity":"43b5b7ff-c97b-4805-8932-8b7da4457e7c","order_by":4,"name":"Itaru Kitahara","email":"data:image/png;base64,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","orcid":"","institution":"University of Tsukuba","correspondingAuthor":true,"prefix":"","firstName":"Itaru","middleName":"","lastName":"Kitahara","suffix":""}],"badges":[],"createdAt":"2026-03-30 06:26:47","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9263053/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9263053/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107704837,"identity":"d73337d0-f97e-4edb-a2e3-94c00087cf45","added_by":"auto","created_at":"2026-04-24 09:00:09","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2024213,"visible":true,"origin":"","legend":"","description":"","filename":"SRSkiinganalysischen2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9263053/v1_covered_2da0f4e4-0b69-4369-b403-6d4828832e2c.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Robust 3D Human Motion Reconstruction from Multi-View Mobile Videos for Quantitative Ski Technique Analysis","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-9263053/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9263053/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Quantitative evaluation of skiing technique in real-world settings is inherently challenging due to complex whole-body coordination, rapid posture transitions, and frequent viewpoint changes during motion. 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