Generating Reconstructable Collaborative Virtual Environments via Graph Matching for Mixed Reality Remote Collaboration

Generating Reconstructable Collaborative Virtual Environments via Graph Matching for Mixed Reality Remote Collaboration | 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 Research Article Generating Reconstructable Collaborative Virtual Environments via Graph Matching for Mixed Reality Remote Collaboration Yaguang Lu, Yong Hu, Huiyan Feng, PengShuai Duan, Xukun Shen This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5193934/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 15 Feb, 2025 Read the published version in The Visual Computer → Version 1 posted 10 You are reading this latest preprint version Abstract Generating Reconstructable Collaborative Virtual Environments (RCVEs) addresses the spatial heterogeneity challenge in Mixed Reality (MR) remote collaboration. Existing methods partition remote spaces into discrete areas, aligning them with local spaces. However, disparities in structural and semantic configurations hinder continuous avatar movement. This paper proposes a Graph Matching-based approach to constrain the spatial topological relationships among discrete areas during RCVEs alignment. An Artificial Potential Fields-based avatar mapping method, named APFBAM, is introduced to rapidly capture and redirect avatars in heterogeneous spaces. Experiments using reconstructed virtual scenes from real-world data demonstrate the effectiveness of these methods in MR remote collaboration. The results indicate that users perceive minimal impact on their experience despite spatial structural differences, validating the approach's suitability for enabling flexible and scalable MR remote collaboration. Mixed Reality Remote Collaboration Heterogeneous Spaces Graph Matching Redirected Walking Full Text Additional Declarations No competing interests reported. Supplementary Files Presentation.mp4 Cite Share Download PDF Status: Published Journal Publication published 15 Feb, 2025 Read the published version in The Visual Computer → Version 1 posted Editorial decision: Revision requested 03 Nov, 2024 Reviews received at journal 02 Nov, 2024 Reviewers agreed at journal 18 Oct, 2024 Reviews received at journal 16 Oct, 2024 Reviewers agreed at journal 14 Oct, 2024 Reviewers agreed at journal 14 Oct, 2024 Reviewers invited by journal 14 Oct, 2024 Editor assigned by journal 03 Oct, 2024 Submission checks completed at journal 03 Oct, 2024 First submitted to journal 02 Oct, 2024 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. 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