A new solution in recovering video to video by hash method

A new solution in recovering video to video by hash method | 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 A new solution in recovering video to video by hash method Aboulfazl Gharahsouflou, Vafa Maihami, Keyhan Khamforoosh This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4669267/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 Every day, with the advancement of visual equipment, large amounts of data generated in the form of films and videos and uploaded to the Internet. Extracting the desired video from an image has become an important challenge, and so, many specialists and experts have tried to provide various solutions, each with its strengths and weaknesses. A content-based video retrieval system consists of three basic steps: key frame extraction, important features extraction and similarity comparison. Hashing is one of the methods used for retrieving data, which is mostly used to retrieve images. In this paper, we propose a new framework using the hashing method to solve the video retrieval problem, which takes advantage of a multidimensional (3D) CNN to obtain the spatial and temporal features of the video. In the proposed method, the features extracted from each key form are transferred using the Hashing function to a binary space by the pre-trained network to receive the compressed binary codes of the video. We have done some test on the two video datasets THUMOS'14 and UCF-101, and the results show that the in proposed method than the existing methods, the value of mAP in the THUMOS'14 dataset increased 0.61% and 0.62%. in UCF-101 dataset. neural network video image feature extraction retrieval 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. 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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-4669267","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":326447186,"identity":"ac4a500b-7e4a-49cc-b591-21f62d60add6","order_by":0,"name":"Aboulfazl Gharahsouflou","email":"","orcid":"","institution":"Islamic Azad University Sanandaj Branch","correspondingAuthor":false,"prefix":"","firstName":"Aboulfazl","middleName":"","lastName":"Gharahsouflou","suffix":""},{"id":326447187,"identity":"c9bb06c2-0b7f-4b4c-97ea-6738c2fa3959","order_by":1,"name":"Vafa Maihami","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5UlEQVRIiWNgGAWjYBACgwOMbUBKQo4NxOPhAZGMDXi1WEK1GBOvxf4AA1hxIlgZDzEOMzt+uO3BzxyL9D72M8Yf3sgwyPM3MLd9wKvlTGK7Ye82idw2nhwzyTk8DIYzDjA2z8Cr5UBimwQvSAtDjhkz0C+MGxgYm/E6zOD8wzbJv9sk0tn43xh/BmqxJ6zlRmKbNNCWBDaJHANpoJZEIrQ8bJOW3SZh2CbxrAzoF4nkGYcJOiz9meTbbXXy8v3Jmz+87bGx7W9vf4xXCypg7JFgYGAmQQMQ/CBN+SgYBaNgFIwMAAC6akQId/vqLgAAAABJRU5ErkJggg==","orcid":"","institution":"Islamic Azad University Sanandaj Branch","correspondingAuthor":true,"prefix":"","firstName":"Vafa","middleName":"","lastName":"Maihami","suffix":""},{"id":326447188,"identity":"c662308b-23db-4f48-97bf-426c01ac2f21","order_by":2,"name":"Keyhan Khamforoosh","email":"","orcid":"","institution":"Islamic Azad University Sanandaj Branch","correspondingAuthor":false,"prefix":"","firstName":"Keyhan","middleName":"","lastName":"Khamforoosh","suffix":""}],"badges":[],"createdAt":"2024-07-01 15:59:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4669267/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4669267/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":77259945,"identity":"216a8772-6567-47e6-8c79-2d490728800f","added_by":"auto","created_at":"2025-02-26 18:46:36","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":662831,"visible":true,"origin":"","legend":"","description":"","filename":"paper21.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4669267/v1_covered_26a6f648-e00a-46cb-9baa-ab3429ae2662.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A new solution in recovering video to video by hash method","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":"neural network, video, image, feature extraction, retrieval","lastPublishedDoi":"10.21203/rs.3.rs-4669267/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4669267/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eEvery day, with the advancement of visual equipment, large amounts of data generated in the form of films and videos and uploaded to the Internet. 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