Boundary Incremental Reconstruction of the Known Space and Unknown Space in Indoor Scenes Based on Surfels

Boundary Incremental Reconstruction of the Known Space and Unknown Space in Indoor Scenes Based on Surfels | 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 Boundary Incremental Reconstruction of the Known Space and Unknown Space in Indoor Scenes Based on Surfels Leili Li, Fuqi Zhang, Yujia Liu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7483649/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract For the three-dimensional reconstruction of indoor scenes, to solve the problems of low point cloud reconstruction accuracy and high space complexity, a surfel-based incremental reconstruction algorithm for the boundary between the known space and the unknown space of the indoor scene is proposed. The algorithm uses the Kinect v1 depth camera to collect actual scene datasets and combines them with public datasets to generate a set of observed surfels, and simulates the boundary between a known space and an unknown space. The algorithm calculates the Boolean union of two bounded volumes, fusing the known volume of the previous frame with the space observed by the current depth image to generate a dense point cloud of the object. The algorithm proposed is effective and advanced, has important promotion significance for the 3D model reconstruction of indoor scenes and buildings and their textures based on surfels, buildings and their textures. boundary incremental reconstruction surfel-based indoor scenes depth camera Kinect v1 dense point cloud collaborative improvement of reconstruction accuracy and robustness Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-7483649","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":510270944,"identity":"d958599f-a3dc-49c0-84eb-42c228e26e40","order_by":0,"name":"Leili Li","email":"","orcid":"","institution":"Jilin Jianzhu University","correspondingAuthor":false,"prefix":"","firstName":"Leili","middleName":"","lastName":"Li","suffix":""},{"id":510270945,"identity":"93498aff-58ef-4c90-bba2-0a3373a16a2d","order_by":1,"name":"Fuqi Zhang","email":"","orcid":"","institution":"Jilin University","correspondingAuthor":false,"prefix":"","firstName":"Fuqi","middleName":"","lastName":"Zhang","suffix":""},{"id":510270946,"identity":"f1f62347-23a2-47c8-a32d-cc08ef5df30a","order_by":2,"name":"Yujia Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzklEQVRIiWNgGAWjYBACPmYQySPBwA+kDgAxYwMhLWwwLZJApQcOEKUFxjA4ALGGCC3sPGbSPDIW8sbHDz88/IHBRnbDAeZnD/A7DKSFR8Jw25k0A6DD0ow3HGAzNyBGC+O2GzwgvxxO3HCAh02CGC32m2eAtfwnXkviBgmwlgPEaGErtpzDI5E8A+SXMwbJxjMPs5nh1cLPf3jjjbc9dbb97Ycff6iosJPtO978DK8WIGCRYOyBsUFBxUxAPUjJB4YfhFWNglEwCkbBCAYAyg1ATHlE46gAAAAASUVORK5CYII=","orcid":"","institution":"Changchun Institute of Technology","correspondingAuthor":true,"prefix":"","firstName":"Yujia","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2025-08-28 23:38:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7483649/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7483649/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103128871,"identity":"c77fc8c3-8fb2-4106-9495-3392064cd60e","added_by":"auto","created_at":"2026-02-21 12:25:00","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":806158,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7483649/v1_covered_82a4a95c-35c3-40f4-a7c4-998e0cb40039.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Boundary Incremental Reconstruction of the Known Space and Unknown Space in Indoor Scenes Based on Surfels","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"boundary incremental reconstruction, surfel-based indoor scenes, depth camera Kinect v1, dense point cloud, collaborative improvement of reconstruction accuracy and robustness","lastPublishedDoi":"10.21203/rs.3.rs-7483649/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7483649/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eFor the three-dimensional reconstruction of indoor scenes, to solve the problems of low point cloud reconstruction accuracy and high space complexity, a surfel-based incremental reconstruction algorithm for the boundary between the known space and the unknown space of the indoor scene is proposed. 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